Irregular Cycles, Ovulatory Disorders, and Cardiometabolic Conditions in a US-Based Digital Cohort.

Importance: Polycystic ovary syndrome (PCOS), characterized by irregular menstrual cycles and hyperandrogenism, is a common ovulatory disorder. Having an irregular cycle is a potential marker for cardiometabolic conditions, but data are limited on whether the associations differ by PCOS status or potential interventions. Objective: To evaluate the association of PCOS, time to regularity since menarche (adolescence), and irregular cycles (adulthood) with cardiometabolic conditions. Design, Setting, and Participants: This cross-sectional study used a large, US-based digital cohort of users of the Apple Research application on their iPhone. Eligibility criteria were having ever menstruated, living in the US, being at age of consent of at least 18 years (or 19 years in Alabama and Nebraska or 21 years in Puerto Rico), and being able to communicate in English. Participants were enrolled between November 14, 2019, and December 13, 2022, and completed relevant surveys. Exposures: Self-reported PCOS diagnosis, prolonged time to regularity (not spontaneously establishing regularity within 5 years of menarche), and irregular cycles. Main Outcomes and Measures: The primary outcome was self-reported cardiometabolic conditions, including obesity, prediabetes, type 1 and 2 diabetes, high cholesterol, hypertension, metabolic syndrome, arrhythmia, congestive heart failure, coronary artery disease, heart attack, heart valve disease, stroke, transient ischemic attack (TIA), deep vein thrombosis, and pulmonary embolism measured using descriptive statistics and logistic regression to estimate prevalence odds ratios (PORs) and 95% CIs. Effect modification by lifestyle factors was also estimated. Results: The study sample (N = 60 789) had a mean (SD) age of 34.5 (11.1) years, with 12.3% having PCOS and 26.3% having prolonged time to regularity. Among a subset of 25 399 participants who completed the hormonal symptoms survey, 25.6% reported irregular cycles. In covariate-adjusted logistic regression models, PCOS was associated with a higher prevalence of all metabolic and several cardiovascular conditions, eg, arrhythmia (POR, 1.37; 95% CI, 1.20-1.55), coronary artery disease (POR, 2.92; 95% CI, 1.95-4.29), heart attack (POR, 1.79; 95% CI, 1.23-2.54), and stroke (POR, 1.66; 95% CI, 1.21-2.24). Among participants without PCOS, prolonged time to regularity was associated with type 2 diabetes (POR, 1.24; 95% CI, 1.05-1.46), hypertension (POR, 1.09; 95% CI, 1.01-1.19), arrhythmia (POR, 1.20; 95% CI, 1.06-1.35), and TIA (POR, 1.33; 95% CI, 1.01-1.73), and having irregular cycles was associated with type 2 diabetes (POR, 1.36; 95% CI, 1.08-1.69), high cholesterol (POR, 1.17; 95% CI, 1.05-1.30), arrhythmia (POR, 1.21; 95% CI, 1.02-1.43), and TIA (POR, 1.56; 95% CI, 1.06-2.26). Some of these associations were modified by high vs low body mass index or low vs high physical activity. Conclusions and Relevance: These findings suggest that PCOS and irregular cycles may be independent markers for cardiometabolic conditions. Early screening and intervention among individuals with irregular menstrual cycles may be beneficial.

First trimester plasma PER- AND Polyfluoroalkyl Substances (PFAS) and blood pressure trajectories across the second and third trimesters of pregnanacy.

BACKGROUND: Evidence suggests that exposure to per- and polyfluoroalkyl substances (PFAS) increases risk of high blood pressure (BP) during pregnancy. Prior studies did not examine associations with BP trajectory parameters (i.e., overall magnitude and velocity) during pregnancy, which is linked to adverse pregnancy outcomes. OBJECTIVES: To estimate associations of multiple plasma PFAS in early pregnancy with BP trajectory parameters across the second and third trimesters. To assess potential effect modification by maternal age and parity. METHODS: In 1297 individuals, we quantified six PFAS in plasma collected during early pregnancy (median gestational age: 9.4 weeks). We abstracted from medical records systolic BP (SBP) and diastolic BP (DBP) measurements, recorded from 12 weeks gestation until delivery. BP trajectory parameters were estimated via Super Imposition by Translation and Rotation modeling. Subsequently, Bayesian Kernel Machine Regression (BKMR) was employed to estimate individual and joint associations of PFAS concentrations with trajectory parameters - adjusting for maternal age, race/ethnicity, pre-pregnancy body mass index, income, parity, smoking status, and seafood intake. We evaluated effect modification by age at enrollment and parity. RESULTS: We collected a median of 13 BP measurements per participant. In BKMR, higher concentration of perfluorooctane sulfonate (PFOS) was independently associated with higher magnitude of overall SBP and DBP trajectories (i.e., upward shift of trajectories) and faster SBP trajectory velocity, holding all other PFAS at their medians. In stratified BKMR analyses, participants with ≥ 1 live birth had more pronounced positive associations between PFOS and SBP velocity, DBP magnitude, and DBP velocity - compared to nulliparous participants. We did not observe significant associations between concentrations of the overall PFAS mixture and either magnitude or velocity of the BP trajectories. CONCLUSION: Early pregnancy plasma PFOS concentrations were associated with altered BP trajectory in pregnancy, which may impact future cardiovascular health of the mother.

Predicting polycystic ovary syndrome with machine learning algorithms from electronic health records.

Introduction: Predictive models have been used to aid early diagnosis of PCOS, though existing models are based on small sample sizes and limited to fertility clinic populations. We built a predictive model using machine learning algorithms based on an outpatient population at risk for PCOS to predict risk and facilitate earlier diagnosis, particularly among those who meet diagnostic criteria but have not received a diagnosis. Methods: This is a retrospective cohort study from a SafetyNet hospital's electronic health records (EHR) from 2003-2016. The study population included 30,601 women aged 18-45 years without concurrent endocrinopathy who had any visit to Boston Medical Center for primary care, obstetrics and gynecology, endocrinology, family medicine, or general internal medicine. Four prediction outcomes were assessed for PCOS. The first outcome was PCOS ICD-9 diagnosis with additional model outcomes of algorithm-defined PCOS. The latter was based on Rotterdam criteria and merging laboratory values, radiographic imaging, and ICD data from the EHR to define irregular menstruation, hyperandrogenism, and polycystic ovarian morphology on ultrasound. Results: We developed predictive models using four machine learning methods: logistic regression, supported vector machine, gradient boosted trees, and random forests. Hormone values (follicle-stimulating hormone, luteinizing hormone, estradiol, and sex hormone binding globulin) were combined to create a multilayer perceptron score using a neural network classifier. Prediction of PCOS prior to clinical diagnosis in an out-of-sample test set of patients achieved an average AUC of 85%, 81%, 80%, and 82%, respectively in Models I, II, III and IV. Significant positive predictors of PCOS diagnosis across models included hormone levels and obesity; negative predictors included gravidity and positive bHCG. Conclusion: Machine learning algorithms were used to predict PCOS based on a large at-risk population. This approach may guide early detection of PCOS within EHR-interfaced populations to facilitate counseling and interventions that may reduce long-term health consequences. Our model illustrates the potential benefits of an artificial intelligence-enabled provider assistance tool that can be integrated into the EHR to reduce delays in diagnosis. However, model validation in other hospital-based populations is necessary.

Evaluation of Menstrual Cycle Tracking Behaviors in the Ovulation and Menstruation Health Pilot Study: Cross-Sectional Study.

BACKGROUND: Menstrual cycle tracking apps (MCTAs) have potential in epidemiological studies of women's health, facilitating real-time tracking of bleeding days and menstrual-associated signs and symptoms. However, information regarding the characteristics of MCTA users versus cycle nontrackers is limited, which may inform generalizability. OBJECTIVE: We compared characteristics among individuals using MCTAs (app users), individuals who do not track their cycles (nontrackers), and those who used other forms of menstrual tracking (other trackers). METHODS: The Ovulation and Menstruation Health Pilot Study tested the feasibility of a digitally enabled evaluation of menstrual health. Recruitment occurred between September 2017 and March 2018. Menstrual cycle tracking behavior, demographic, and general and reproductive health history data were collected from eligible individuals (females aged 18-45 years, comfortable communicating in English). Menstrual cycle tracking behavior was categorized in 3 ways: menstrual cycle tracking via app usage, that via other methods, and nontracking. Demographic factors, health conditions, and menstrual cycle characteristics were compared across the menstrual tracking method (app users vs nontrackers, app users vs other trackers, and other trackers vs nontrackers) were assessed using chi-square or Fisher exact tests. RESULTS: In total, 263 participants met the eligibility criteria and completed the digital survey. Most of the cohort (n=191, 72.6%) was 18-29 years old, predominantly White (n=170, 64.6%), had attained 4 years of college education or higher (n= 209, 79.5%), and had a household income below US $50,000 (n=123, 46.8%). Among all participants, 103 (39%) were MCTA users (app users), 97 (37%) did not engage in any tracking (nontrackers), and 63 (24%) used other forms of tracking (other trackers). Across all groups, no meaningful differences existed in race and ethnicity, household income, and education level. The proportion of ever-use of hormonal contraceptives was lower (n=74, 71.8% vs n=87, 90%, P=.001), lifetime smoking status was lower (n=6, 6% vs n=15, 17%, P=.04), and diagnosis rate of gastrointestinal reflux disease (GERD) was higher (n=25, 24.3% vs n=12, 12.4%, P=.04) in app users than in nontrackers. The proportions of hormonal contraceptives ever used and lifetime smoking status were both lower (n=74, 71.8% vs n=56, 88.9%, P=.01; n=6, 6% vs n=11, 17.5%, P=.02) in app users than in other trackers. Other trackers had lower proportions of ever-use of hormonal contraceptives (n=130, 78.3% vs n=87, 89.7%, P=.02) and higher diagnostic rates of heartburn or GERD (n=39, 23.5% vs n=12, 12.4%, P.03) and anxiety or panic disorder (n=64, 38.6% vs n=25, 25.8%, P=.04) than nontrackers. Menstrual cycle characteristics did not differ across all groups. CONCLUSIONS: Our results suggest that app users, other trackers, and nontrackers are largely comparable in demographic and menstrual cycle characteristics. Future studies should determine reasons for tracking and tracking-related behaviors to further understand whether individuals who use MCTAs are comparable to nontrackers.

Abnormal uterine bleeding patterns determined through menstrual tracking among participants in the Apple Women's Health Study.

BACKGROUND: Use of menstrual tracking data to understand abnormal bleeding patterns has been limited because of lack of incorporation of key demographic and health characteristics and confirmation of menstrual tracking accuracy. OBJECTIVE: This study aimed to identify abnormal uterine bleeding patterns and their prevalence and confirm existing and expected associations between abnormal uterine bleeding patterns, demographics, and medical conditions. STUDY DESIGN: Apple Women's Health Study participants from November 2019 through July 2021 who contributed menstrual tracking data and did not report pregnancy, lactation, use of hormones, or menopause were included in the analysis. Four abnormal uterine bleeding patterns were evaluated: irregular menses, infrequent menses, prolonged menses, and irregular intermenstrual bleeding (spotting). Monthly tracking confirmation using survey responses was used to exclude inaccurate or incomplete digital records. We investigated the prevalence of abnormal uterine bleeding stratified by demographic characteristics and used logistic regression to evaluate the relationship of abnormal uterine bleeding to a number of self-reported medical conditions. RESULTS: There were 18,875 participants who met inclusion criteria, with a mean age of 33 (standard deviation, 8.2) years, mean body mass index of 29.3 (standard deviation, 8.0), and with 68.9% (95% confidence interval, 68.2-69.5) identifying as White, non-Hispanic. Abnormal uterine bleeding was found in 16.4% of participants (n=3103; 95% confidence interval, 15.9-17.0) after accurate tracking was confirmed; 2.9% had irregular menses (95% confidence interval, 2.7-3.1), 8.4% had infrequent menses (95% confidence interval, 8.0-8.8), 2.3% had prolonged menses (95% confidence interval, 2.1-2.5), and 6.1% had spotting (95% confidence interval, 5.7-6.4). Black participants had 33% higher prevalence (prevalence ratio, 1.33; 95% confidence interval, 1.09-1.61) of infrequent menses compared with White, non-Hispanic participants after controlling for age and body mass index. The prevalence of infrequent menses was increased in class 1, 2, and 3 obesity (class 1: body mass index, 30-34.9; prevalence ratio, 1.31; 95% confidence interval, 1.13-1.52; class 2: body mass index, 35-39.9; prevalence ratio, 1.25; 95% confidence interval, 1.05-1.49; class 3: body mass index, >40; prevalence ratio, 1.51; 95% confidence interval, 1.21-1.88) after controlling for age and race/ethnicity. Those with class 3 obesity had 18% higher prevalence of abnormal uterine bleeding compared with healthy-weight participants (prevalence ratio, 1.18; 95% confidence interval, 1.02-1.38). Participants with polycystic ovary syndrome had 19% higher prevalence of abnormal uterine bleeding compared with participants without this condition (prevalence ratio, 1.19; 95% confidence interval, 1.08-1.31). Participants with hyperthyroidism (prevalence ratio, 1.34; 95% confidence interval, 1.13-1.59) and hypothyroidism (prevalence ratio, 1.17; 95% confidence interval, 1.05-1.31) had a higher prevalence of abnormal uterine bleeding, as did those reporting endometriosis (prevalence ratio, 1.28; 95% confidence interval, 1.12-1.45), cervical dysplasia (prevalence ratio, 1.20; 95% confidence interval, 1.03-1.39), and fibroids (prevalence ratio, 1.14; 95% confidence interval, 1.00-1.30). CONCLUSION: In this cohort, abnormal uterine bleeding was present in 16.4% of those with confirmed menstrual tracking. Black or obese participants had increased prevalence of abnormal uterine bleeding. Participants reporting conditions such as polycystic ovary syndrome, thyroid disease, endometriosis, and cervical dysplasia had a higher prevalence of abnormal uterine bleeding.

Optimization of assisted reproductive technology outcomes in patients with polycystic ovarian syndrome: updates and unanswered questions.

PURPOSE OF REVIEW: Narrative review of recent literature on optimization of assisted reproduction technology outcomes in patients with polycystic ovarian syndrome (PCOS). RECENT FINDINGS: The key areas of focus include pre cycle treatment with the goal of cohort synchronization, methods of ovulation suppression and trigger medication. There is no definitive evidence that precycle treatment with combined oral contraceptives (COCs) or progestins improve or negatively impact in vitro fertilization outcomes in patients with PCOS. The reviewed evidence supports consideration of progestins as suppression of premature ovulation in patients with PCOS as an alternative to gonadotropin releasing hormone (GnRH) antagonist if a freeze all protocol is planned. There is limited prospective evidence in PCOS populations regarding use of a dual trigger using GnRH agonist and human chorionic gonadotropin (hCG). SUMMARY: This review has implications for clinical practice regarding ovarian stimulation protocols for patients with PCOS. We also identified areas of research need including the further exploration of the value of pre cycle COC or progestin use in a PCOS population, also the use of GnRH agonist in combination with hCG in a well defined PCOS population and using GnRH agonist trigger alone as a control.

Digital Global Recruitment for Women's Health Research: Cross-sectional Study.

BACKGROUND: With the increased popularity of mobile menstrual tracking apps and boosted Facebook posts, there is a unique opportunity to recruit research study participants from across the globe via these modalities to evaluate women's health. However, no studies to date have assessed the feasibility of using these recruitment sources for epidemiological research on ovulation and menstruation. OBJECTIVE: The objective of this study was to assess the feasibility of recruiting a diverse sample of women to an epidemiological study of ovulation and menstruation (OM) health (OM Global Health Study) using digital recruitment sources. The feasibility and diversity were assessed via click and participation rates, geographic location, BMI, smoking status, and other demographic information. METHODS: Participants were actively recruited via in-app messages using the menstrual tracking app Clue (BioWink GmbH) and a boosted Facebook post by DivaCup (Diva International Inc.). Other passive recruitment methods also took place throughout the recruitment period (eg, email communications, blogs, other social media). The proportion of participants who visited the study website after viewing and clicking the hypertext link (click rates) in the in-app messages and boosted Facebook post and the proportion of participants who completed the surveys per the number of completed consent and eligibility screeners (participation rates) were used to quantify the success of recruiting participants to the study website and study survey completion, respectively. Survey completion was defined as finishing the pregnancy and birth history section of the OM Global Health Study questionnaire. RESULTS: The recruitment period was from February 27, 2018, through January 24, 2020. In-app messages and the boosted Facebook post were seen by 104,000 and 21,400 people, respectively. Overall, 215 participants started the OM Global Health Study survey, of which 140 (65.1%), 39 (18.1%), and 36 (16.8%) participants were recruited via the app, the boosted Facebook post, and other passive recruitment methods, respectively. The click rate via the app was 18.9% (19,700 clicks/104,000 ad views) and 1.6% via the boosted Facebook post (340 clicks/21,400 ad views.) The overall participation rate was 44.6% (198/444), and the average participant age was 21.8 (SD 6.1) years. In terms of geographic and racial/ethnic diversity, 91 (44.2%) of the participants resided outside the United States and 147 (70.7%) identified as non-Hispanic White. In-app recruitment produced the most geographically diverse stream, with 44 (32.8%) of the 134 participants in Europe, 77 (57.5%) in North America, and 13 (9.8%) in other parts of the world. Both human error and nonhuman procedural breakdowns occurred during the recruitment process, including a computer programming error related to age eligibility and a hacking attempt by an internet bot. CONCLUSIONS: In-app messages using the menstrual tracking app Clue were the most successful method for recruiting participants from many geographic regions and producing the greatest numbers of started and completed surveys. This study demonstrates the utility of digital recruitment to enroll participants from diverse geographic locations and provides some lessons to avoid technical recruitment errors in future digital recruitment strategies for epidemiological research.

Untargeted metabolomics reveals that multiple reproductive toxicants are present at the endometrium.

BACKGROUND: Recent epidemiologic research shows many environmental chemicals exhibit endocrine disrupting effects on the female reproductive system. Few studies have examined exposure at reproductive organs. Our aim was to perform a preliminary untargeted metabolomic characterization of menstrual blood, a novel biofluid, to identify environmental toxins present in the endometrium and evaluate the suitability of this sample type for exposome research. METHODS: Whole blood menstrual samples were collected from four women using a menstrual cup. Samples were analyzed for small molecules that include both environmental chemicals and endogenous metabolites using untargeted liquid chromatography with high-resolution mass spectrometry (LC-HRMS). Principal component analysis (PCA) and ANOVA was used to identify differences within and between individuals' menstrual blood metabolomic profiles, and the influence of the sample processing method. To assess the presence of environmental exposures, LC-HRMS chemical profiles were matched to the ToxCast chemical database, which includes 4557 commonly used commercial chemicals. Select compounds were confirmed by comparison to reference standards. RESULTS: PCA of metabolome profiles showed analysis of menstrual blood samples were highly reproducible, with high variability in detected metabolites between participants and low variability between analytical replicates of an individual's sample. Endogenous metabolites detected in menstrual blood samples achieved good coverage of the human blood metabolome. We found 1748 annotations for environmental chemicals, including suspected reproductive toxicants such as phenols, parabens, phthalates, and organochlorines. Storage temperature for the first 24 h did not significantly influence global metabolomic profiles. CONCLUSION: Our results show chemical exposures linked to reproductive toxicity and endocrine disruption are present in menstrual blood, a sampling medium for the endometrium.

Exploring the causes of semen quality changes post-bariatric surgery: a focus on endocrine-disrupting chemicals.

Rapid weight loss promoted by bariatric surgery (BS) can release accumulated lipophilic endocrine-disrupting chemicals (EDCs), making these chemicals systemically available. Men typically have a higher EDC body burden and lose more weight post-BS than women, which may put male BS patients at high risk for testicular toxicity. In this review, we analyze the impacts of BS on semen parameters with a particular focus on the potential effects of EDCs. After BS, serum EDC concentrations progressively increase; and there is evidence that semen parameters deteriorate after BS. Although elevated serum EDC concentrations are associated with inferior sperm parameters, links between semen parameters and EDCs post-BS have not been studied. Understanding these potential associations requires adequately powered studies, particularly within prospective longitudinal cohorts with long-term follow-up for sperm parameters, nutritional status, sex-hormones levels and serum EDC concentrations. Studying BS patients prospectively provides the important opportunity to evaluate dose-response effects of EDC serum concentrations on sperm quality and function. Research is also needed to identify critical chemical exposure periods post-BS to inform reproductive decisions, including consideration of sperm preservation before surgery.

Fine particulate matter and polycystic ovarian morphology.

BACKGROUND: Polycystic ovary morphology (PCOM) is an ultrasonographic finding that can be present in women with ovulatory disorder and oligomenorrhea due to hypothalamic, pituitary, and ovarian dysfunction. While air pollution has emerged as a possible disrupter of hormone homeostasis, limited research has been conducted on the association between air pollution and PCOM. METHODS: We conducted a longitudinal cohort study using electronic medical records data of 5,492 women with normal ovaries at the first ultrasound that underwent a repeated pelvic ultrasound examination during the study period (2004-2016) at Boston Medical Center. Machine learning text algorithms classified PCOM by ultrasound. We used geocoded home address to determine the ambient annual average PM2.5 exposures and categorized into tertiles of exposure. We used Cox Proportional Hazards models on complete data (n = 3,994), adjusting for covariates, and additionally stratified by race/ethnicity and body mass index (BMI). RESULTS: Cumulative exposure to PM2.5 during the study ranged from 4.9 to 17.5 µg/m3 (mean = 10.0 µg/m3). On average, women were 31 years old and 58% were Black/African American. Hazard ratios and 95% confidence intervals (CI) comparing the second and third PM2.5 exposure tertile vs. the reference tertile were 1.12 (0.88, 1.43) and 0.89 (0.62, 1.28), respectively. No appreciable differences were observed across race/ethnicity. Among women with BMI ≥ 30 kg/m2, we observed weak inverse associations with PCOM for the second (HR: 0.93, 95% CI: 0.66, 1.33) and third tertiles (HR: 0.89, 95% CI: 0.50, 1.57). CONCLUSIONS: In this study of reproductive-aged women, we observed little association between PM2.5 concentrations and PCOM incidence. No dose response relationships were observed nor were estimates appreciably different across race/ethnicity within this clinically sourced cohort.

Ultraviolet radiation and age at natural menopause in a nationwide, prospective US cohort.

BACKGROUND: Solar ultraviolet radiation (UV) is a critical environmental factor for dermal conversion of vitamin D, which is suggested to support reproductive health. However, current epidemiological studies have reported conflicting results on the associations between vitamin D levels and ovarian reserve. Further, few studies have considered UV exposure and reproductive aging, which is closely related to declined ovarian reserve. OBJECTIVES: We sought to examine the associations of long-term UV exposure and age at natural menopause in a large, nationwide, prospective cohort. METHODS: Participants in the Nurses' Health Study II (NHS II) who were premenopausal at age 40 were included and followed through 2015. Erythemal UV radiation from a high-resolution geospatial model was linked to the participants' residential histories. Early-life UV was estimated using the reported state of residence at birth, age 15, and age 30. We used time-varying Cox proportional hazards models to estimate the hazard ratio (HR) and 95% confidence intervals (CIs) for natural menopause, adjusting for potential confounders and predictors of menopause. RESULTS: A total of 63,801 women reported natural menopause across the 1,051,185 person-years of follow-up among 105,631 eligible participants. We found very modest associations with delayed menopause for long-term UV exposure (adjusted HR comparing highest to lowest quartile of cumulative average UV: 0.96, 95% CI: 0.94, 0.99). There was a suggestive inverse association between UV at age 30 with menopause (adjusted HR comparing highest to lowest quartile: 0.97, 95% CI: 0.95, 1.00) but not with UV at birth and age 15. CONCLUSIONS: Solar UV exposure in adulthood was modestly associated with later onset of menopause. Although consistent with previous findings on vitamin D intake and menopause in the same population, these weak associations found in this study may not be of clinical relevance.

The effects of delta-9-tetrahydrocannabinol exposure on female menstrual cyclicity and reproductive health in rhesus macaques.

OBJECTIVE: To determine the dose-dependent effect of contemporary marijuana exposure on female menstrual cyclicity and reproductive endocrine physiology in a nonhuman primate model. DESIGN: Research animal study. SETTING: Research institute environment. ANIMALS: Adult female rhesus macaques (6-12 years of age; n = 8). INTERVENTIONS: Daily delta-9-tetrahydrocannabinol (THC) edible at medically and recreationally relevant contemporary doses. MAIN OUTCOME MEASURES: Menstrual cycle length (MCL), anti-Müllerian hormone, prolactin, basal follicle-stimulating hormone (FSH), estradiol (E2) and progesterone, luteinizing hormone (LH), and thyroid-stimulating hormone. RESULTS: The average before THC weight was 6.9 kg (standard deviation, 0.8), and at the highest THC dosing, the average weight was 7.2 kg (standard deviation, 0.8). With increasing THC dosing, MCL and FSH concentrations increased, while basal E2 concentration was stable. The average MCL concentration increased 4.0 days for each mg/7 kg/day of THC (95% CI, 1.4-6.6 days). Follicle-stimulating hormone concentration increased significantly with increasing THC dose, 0.34 ng/mL for each mg/7 kg/day of THC (95% CI, 0.14-0.57 ng/mL). No significant trends were observed between THC dosing and average basal progesterone, anti-Müllerian hormone, prolactin, LH, or thyroid-stimulating hormone concentrations. CONCLUSIONS: In rhesus macaques, a dose response toward increased MCL and basal FSH concentrations but plateau of basal E2 and LH concentrations was observed with increasing THC dosing, suggesting ovulatory dysfunction. Further studies are needed to determine the effects of a longer duration of exposure and whether the significant increase in MCL and FSH concentrations results in reduced fecundity.

Associations of long-term exposure to environmental noise and outdoor light at night with age at natural menopause in a US women cohort.

Previous studies have suggested noise, especially at night time, and light at night (LAN) could cause neuroendocrine disturbance and circadian disruption, which may lead to ovarian follicle atresia and earlier onset of menopause. However, no study to date has directly investigated the associations of exposure to these factors and menopausal age. METHODS: Premenopausal women from the Nurses' Health Study II (NHS II) were followed from age 40 through 2015. Median daytime and nighttime anthropogenic noise and outdoor LAN exposure were measured from a geospatial prediction model and satellite images, respectively, at residential addresses throughout the follow-up. Time-varying Cox proportional hazard models were used to calculate the hazard ratios and 95% confidence intervals, adjusting for individual lifestyle, reproductive history, and neighborhood socioeconomic factors. Possible effect modification by region, smoking status, body mass index, race/ethnicity, history of rotating shift work, and census tract population density and median income was examined. RESULTS: A total of 63,380 of 105,326 women self-reported natural menopause during 1,043,298 person-years of follow-up. No associations were found for noise (both daytime and nighttime) and outdoor LAN exposure with age at natural menopause (hazard ratios = 0.99-1.00) in the fully adjusted models. Sensitivity analyses showed similar null associations. No meaningful effect modification was found for region, smoking status, body mass index, race/ethnicity, history of rotating shift work, and census tract socioeconomic measures in stratified analyses. CONCLUSION: No associations were found between environmental noise and outdoor LAN exposure in mid-adulthood and menopausal age in this cohort of US women.

Hormonal activity in commonly used Black hair care products: evaluating hormone disruption as a plausible contribution to health disparities.

BACKGROUND: Certain types of hair products are more commonly used by Black women. Studies show hair products contain several endocrine-disrupting chemicals that are associated with adverse health outcomes. As chemical mixtures of endocrine disruptors, hair products may be hormonally active, but this remains unclear. OBJECTIVE: To assess the hormonal activity of commonly used Black hair products. METHODS: We identified six commonly used hair products (used by >10% of the population) from the Greater New York Hair Products Study. We used reporter gene assays (RGAs) incorporating natural steroid receptors to evaluate estrogenic, androgenic, progestogenic, and glucocorticoid hormonal bioactivity employing an extraction method using bond elution prior to RGA assessment at dilutions from 50 to 500. RESULTS: All products displayed hormonal activity, varying in the amount and effect. Three samples showed estrogen agonist properties at levels from 12.5 to 20 ng/g estradiol equivalent concentrations All but one sample showed androgen antagonist properties at levels from 20 to 25 ng/g androgen equivalent concentrations. Four samples showed antagonistic and agonistic properties to progesterone and glucocorticoid. SIGNIFICANCE: Hair products commonly used by Black women showed hormonal activity. Given their frequent use, exposure to hormonally active products could have implications for health outcomes and contribute to reproductive and metabolic health disparities.

Multimodal Recruitment to Study Ovulation and Menstruation Health: Internet-Based Survey Pilot Study.

BACKGROUND: Multimodal recruitment strategies are a novel way to increase diversity in research populations. However, these methods have not been previously applied to understanding the prevalence of menstrual disorders such as polycystic ovary syndrome. OBJECTIVE: The purpose of this study was to test the feasibility of recruiting a diverse cohort to complete a web-based survey on ovulation and menstruation health. METHODS: We conducted the Ovulation and Menstruation Health Pilot Study using a REDCap web-based survey platform. We recruited 200 women from a clinical population, a community fair, and the internet. RESULTS: We recruited 438 women over 29 weeks between September 2017 and March 2018. After consent and eligibility determination, 345 enrolled, 278 started (clinic: n=43; community fair: n=61; internet: n=174), and 247 completed (clinic: n=28; community fair: n=60; internet: n=159) the survey. Among all participants, the median age was 25.0 (SD 6.0) years, mean BMI was 26.1 kg/m2 (SD 6.6), 79.7% (216/271) had a college degree or higher, and 14.6% (37/254) reported a physician diagnosis of polycystic ovary syndrome. Race and ethnicity distributions were 64.7% (176/272) White, 11.8% (32/272) Black/African American, 7.7% (21/272) Latina/Hispanic, and 5.9% (16/272) Asian individuals; 9.9% (27/272) reported more than one race or ethnicity. The highest enrollment of Black/African American individuals was in clinic (17/42, 40.5%) compared to 1.6% (1/61) in the community fair and 8.3% (14/169) using the internet. Survey completion rates were highest among those who were recruited from the internet (159/174, 91.4%) and community fairs (60/61, 98.4%) compared to those recruited in clinic (28/43, 65.1%). CONCLUSIONS: Multimodal recruitment achieved target recruitment in a short time period and established a racially diverse cohort to study ovulation and menstruation health. There were greater enrollment and completion rates among those recruited via the internet and community fair.

Long-term exposure to particulate matter and roadway proximity with age at natural menopause in the Nurses' Health Study II Cohort.

Evidence has shown associations between air pollution and traffic-related exposure with accelerated aging, but no study to date has linked the exposure with age at natural menopause, an important indicator of reproductive aging. In this study, we sought to examine the associations of residential exposure to ambient particulate matter (PM) and distance to major roadways with age at natural menopause in the Nurses' Health Study II (NHS II), a large, prospective female cohort in US. A total of 105,996 premenopausal participants in NHS II were included at age 40 and followed through 2015. Time-varying residential exposures to PM10, PM2.5-10, and PM2.5 and distance to roads was estimated. We calculated hazard ratios (HR) and 95% confidence intervals (CIs) for natural menopause using Cox proportional hazard models adjusting for potential confounders and predictors of age at menopause. We also examined effect modification by region, smoking, body mass, physical activity, menstrual cycle length, and population density. There were 64,340 reports of natural menopause throughout 1,059,229 person-years of follow-up. In fully adjusted models, a 10 µg/m3 increase in the cumulative average exposure to PM10 (HR: 1.02, 95% CI: 1.00, 1.04), PM2.5-10 (HR: 1.03, 95% CI: 1.00, 1.05), and PM2.5 (HR: 1.03, 95% CI: 1.00, 1.06) and living within 50 m to a major road at age 40 (HR: 1.03, 95%CI: 1.00, 1.06) were associated with slightly earlier menopause. No statistically significant effect modification was found, although the associations of PM were slightly stronger for women who lived in the West and for never smokers. To conclude, we found exposure to ambient PM and traffic in midlife was associated with slightly earlier onset of natural menopause. Our results support previous evidence that exposure to air pollution and traffic may accelerate reproductive aging.

Data mining polycystic ovary morphology in electronic medical record ultrasound reports.

BACKGROUND: Polycystic ovary syndrome (PCOS) is characterized by hyperandrogenemia, oligo-anovulation, and numerous ovarian cysts. Hospital electronic medical records provide an avenue for investigating polycystic ovary morphology commonly seen in PCOS at a large scale. The purpose of this study was to develop and evaluate the performance of two machine learning text algorithms, for classification of polycystic ovary morphology (PCOM) in pelvic ultrasounds. METHODS: Pelvic ultrasound reports from patients at Boston Medical Center between October 1, 2003 and December 12, 2016 were included for analysis, which resulted in 39,093 ultrasound reports from 25,535 unique women. Following the 2003 Rotterdam Consensus Criteria for polycystic ovary syndrome, 2000 randomly selected ultrasounds were expert labeled for PCOM status as present, absent, or unidentifiable (not able to be determined from text alone). An ovary was marked as having PCOM if there was mention of numerous peripheral follicles or if the volume was greater than 10 ml in the absence of a dominant follicle or other confounding pathology. Half of the labeled data was used to develop and refine the algorithms, and the other half was used as a test set for evaluating its accuracy. RESULTS: On the evaluation set of 1000 random US reports, the accuracy of the classifiers were 97.6% (95% CI: 96.5, 98.5%) and 96.1% (94.7, 97.2%). Both models were more adept at identifying PCOM-absent ultrasounds than either PCOM-unidentifiable or PCOM-present ultrasounds. The two classifiers estimated prevalence of PCOM within the whole set of 39,093 ultrasounds to be 44% PCOM-absent, 32% PCOM-unidentifiable, and 24% PCOM-present. CONCLUSIONS: Although accuracy measured on the test set and inter-rater agreement between the two classifiers (Cohen's Kappa = 0.988) was high, a major limitation of our approach is that it uses the ultrasound report text as a proxy and does not directly count follicles from the ultrasound images themselves.

Cohort profile: The MULTI sTUdy Diabetes rEsearch (MULTITUDE) consortium.

PURPOSE: Globally, the age-standardised prevalence of type 2 diabetes mellitus (T2DM) has nearly doubled from 1980 to 2014, rising from 4.7% to 8.5% with an estimated 422 million adults living with the chronic disease. The MULTI sTUdy Diabetes rEsearch (MULTITUDE) consortium was recently established to harmonise data from 17 independent cohort studies and clinical trials and to facilitate a better understanding of the determinants, risk factors and outcomes associated with T2DM. PARTICIPANTS: Participants range in age from 3 to 88 years at baseline, including both individuals with and without T2DM. MULTITUDE is an individual-level pooled database of demographics, comorbidities, relevant medications, clinical laboratory values, cardiac health measures, and T2DM-associated events and outcomes across 45 US states and the District of Columbia. FINDINGS TO DATE: Among the 135 156 ongoing participants included in the consortium, almost 25% (33 421) were diagnosed with T2DM at baseline. The average age of the participants was 54.3, while the average age of participants with diabetes was 64.2. Men (55.3%) and women (44.6%) were almost equally represented across the consortium. Non-whites accounted for 31.6% of the total participants and 40% of those diagnosed with T2DM. Fewer individuals with diabetes reported being regular smokers than their non-diabetic counterparts (40.3% vs 47.4%). Over 85% of those with diabetes were reported as either overweight or obese at baseline, compared with 60.7% of those without T2DM. We observed differences in all-cause mortality, overall and by T2DM status, between cohorts. FUTURE PLANS: Given the wide variation in demographics and all-cause mortality in the cohorts, MULTITUDE consortium will be a unique resource for conducting research to determine: differences in the incidence and progression of T2DM; sequence of events or biomarkers prior to T2DM diagnosis; disease progression from T2DM to disease-related outcomes, complications and premature mortality; and to assess race/ethnicity differences in the above associations.

Marijuana use and fecundability in a North American preconception cohort study.

BACKGROUND: The influence of marijuana use on human fertility has not been well studied. We evaluated the association between female and male use of marijuana and fecundability in Pregnancy Study Online, a prospective cohort of North American couples. METHODS: Female participants completed a baseline questionnaire on which they reported lifestyle and behavioural factors, including frequency of marijuana use within the previous 2 months. Male partners completed an optional baseline questionnaire on similar factors, including marijuana use. Women completed follow-up questionnaires every 8 weeks for 12 months or until pregnancy, initiation of fertility treatment or loss to follow-up, whichever came first. The analysis was restricted to 4194 women (1125 couples) with ≤6 cycles of pregnancy attempt time at study enrolment (2013-2017). Fecundability ratios (FR) and 95% CIs were estimated using proportional probabilities regression models, with adjustment for potential confounders. RESULTS: Men (14.2%) were more likely than women (11.6%) to be marijuana users. FRs for female marijuana use <1 and ≥1 time/week relative to non-use were 0.99 (95% CI 0.85 to 1.16) and 0.98 (95% CI 0.80 to 1.20), respectively. FRs for male marijuana use <1 and ≥1 time/week relative to non-use were 0.87 (95% CI 0.66 to 1.15) and 1.24 (95% CI 0.90 to 1.70), respectively. Associations for frequent marijuana use (≥1 time/week) were attenuated among non-smoking men (FR=1.21, 95% CI 0.84 to 1.74), but stronger among men reporting intercourse ≥4 times/week (FR=1.35, 95% CI 0.72 to 2.53). CONCLUSIONS: In this preconception cohort study, there was little overall association between female or male marijuana use and fecundability.