To examine birth outcomes between children conceived with in vitro fertilization (IVF) or intrauterine insemination (IUI) and sibling births from unassisted conceptions. Retrospective sibling cohort. Live born children conceived via IVF, with or without intracytoplasmic sperm injection, or IUI at the Utah Center for Reproductive Medicine, 1999-2018, and sibling births from unassisted conceptions (born 1985-2018). The main analysis included singleton births (460 IVF, 666 IUI, and 1,579 unassisted siblings). Exposure: In vitro fertilization, with or without intracytoplasmic sperm injection, or IUI. Preterm birth, low birth weight, small for gestational age, large for gestational age (LGA), and major congenital anomalies. Compared with unassisted siblings, singleton children conceived via IVF had gestational ages shorter by nearly half a week (95% confidence interval [CI], -0.6 to -0.3), birth weights of 72.1 g lower (95% CI, -118.8 to -25.4), and higher proportions of preterm birth (IVF, 11.1%; IUI, 8.7%; unassisted siblings, 6.8%), LGA (IVF, 9.1%; IUI, 4.5%; unassisted siblings, 5.9%), and major congenital anomalies (IVF, 3.7%; IUI, 2.0%; unassisted siblings, 1.4%). Models adjusted for maternal age, infant sex, infant birth year, previous pregnancy, and birth order showed that children conceived via IVF were more likely to be preterm (adjusted risk ratio [aRR], 1.6; 95% CI, 1.2-2.2; absolute difference, 4.3%) and LGA (aRR, 1.8; 95% CI, 1.2-2.5; absolute difference, 3.2%). Children conceived via IVF had a higher risk of major congenital anomalies than unassisted siblings adjusted for maternal age, infant sex, and birth order (aRR, 1.9; 95% CI, 1.0-3.8; absolute difference, 2.3%). Children conceived via IUI had birth weights 55.8 g lower (95% CI, -95.6 to -15.9) than unassisted siblings. We observed an increased risk of preterm birth, low birth weight, LGA, and major congenital anomalies among singleton children conceived with IVF compared with that among unassisted siblings; however, absolute differences remain small. For children conceived via IUI, lower birth weights were observed. These results suggest that treatment-related factors in addition to underlying subfertility may contribute to adverse birth outcomes.
Background Severe COVID-19 results in substantial economic burden and impacts quality of life. Assessing how non-hospitalized COVID-19 impacts health utilities during acute infection and long term is important to estimate the full economic impact of SARS-CoV-2 infection. Methods We analyzed EQ-5D-3L survey data from SARS-CoV-2 infected adults (aged ≥16 years) and children (aged 8-15 years) from three community and household cohorts in the United States (2020-2022). EQ-5D-3L scores were analyzed at three time points after symptom onset or first positive SARS-CoV-2 test result and converted to health utilities on a scale of 0-1 (1=perfect health). Among adults, regression models were used to compare differences in health utility by demographic/clinical characteristics. Results Among 538 SARS-CoV-2 non-hospitalized asymptomatic/symptomatic infections from 575 adults with EQ-5D-3L surveys, mean utilities were near 1 throughout the observation period. During 0-14 days, vaccinated participants had higher health utilities (Beta:0.57, 95% CI:0.07,1.07). Seeking medical care and having gastrointestinal symptoms (vs. none), were associated with lower health utilities (Beta, 95% CI:-0.96, −1.60, −0.31; and −0.76, −1.30, −0.21 respectively). During 15-30 days, unemployment was associated with lower health utility (Beta:-0.64, 95% CI:-1.15,-0.14). During 31-90 days, underlying conditions were associated with lower health utilities (Beta:-0.32, 95% CI:-0.54, −0.09). Results for children were similar to adults. Conclusion Non-hospitalized COVID-19 may have minimal overall impact on quality of life; however, health utilities differed by vaccination status, presence of gastrointestinal symptoms, employment status, and presence of underlying conditions. Vaccination may play an important role in minimizing illness impact from SARS-CoV-2 infection. Key points Severe COVID-19 illness causes substantial economic burden and impacts on quality of life; however, the incidence of non-hospitalized COVID-19 is far greater. Assessing how non-hospitalized COVID-19 impacts health during acute infection and long term is important to understand the full impact of SARS-CoV-2 infection. This study utilizes the EQ-5D-3L, a standardized generic preference-based instrument used in population health studies, to estimate health utilities at multiple time points following SARS-CoV-2 infection. The study also examines demographic/medical characteristics that are associated with health utility over time. While mean health utilities were high for all infection periods regardless of age, health utility was lower at varying time points post-infection among adults who sought medical care, reported gastrointestinal symptoms, were unemployed, and with underlying conditions. Vaccinated adults (vs. unvaccinated) had higher health utility and were less likely to report reduced health. Findings can be used as inputs for economic evaluation and assessing impact of interventions for non-hospitalized SARS-CoV-2 illness, such as vaccination.
Understanding and mitigating health risks from poor indoor air quality, particularly fine particulate matter (PM2.5), is critical, yet conventional monitoring methods are costly and require skilled operators. Low-cost sensors (LCS) offer an accessible alternative; however, their accuracy under varying environmental conditions remains uncertain. This study evaluates how humidity, temperature, deployment duration, and concentration levels affect the calibration accuracy of low-cost PM2.5 monitors. Nineteen Plantower PMS 3003 sensors deployed in 11 Salt Lake County homes participating in the Green & Healthy Homes Initiative were calibrated before and after residential deployment using a TSI DustTrak aerosol monitor. Linear and Lasso regression analyses were performed to evaluate the influence of environmental factors on calibration parameters. Significant variability was observed in environmental conditions. Higher humidity (p = 0.0197) and longer deployment durations (p = 0.0178) significantly altered calibration slopes, while mean PM2.5 exposure (p = 0.0040) was strongly associated with intercept adjustments. These findings emphasize the need to account for environmental factors in calibration models to improve LCS accuracy and reliability. Environmental conditions significantly impact the performance of low-cost PM2.5 sensors. Modeling these impacts can streamline the calibration process, making it more efficient and cost-effective. Future research should focus on refining calibration models and exploring additional environmental factors to optimize LCS performance.
Knowledge of the fertile and infertile phases of the menstrual cycle can be applied to conceive or to avoid pregnancy. Fertility intentions and sexual behaviors during the fertile time may influence whether and when pregnancy occurs. The Creighton Model FertilityCare System (CrMS) is a specific system of fertility appreciation used to conceive or to avoid pregnancy. The objective of this paper is to report intentions, behaviors, and pregnancy rates during use of the CrMS among couples who initially intended to avoid pregnancy.Data and methodsWe analyzed a prospective cohort study conducted in 17 CrMS centers across the USA and Canada, following 296 couples for up to one year after onset of initial use of the CrMS to avoid pregnancy. Baseline data included demographics, motivations, and pregnancy intentions for each partner. Couples contributed 2894 menstrual cycles, most of which had data collected (by questionnaires and daily diary) on cycle-specific pregnancy intentions, days of potential fertility, and fertility behaviors. Pregnancies were prospectively actively ascertained. We found a high concordance (91%) in cycle pregnancy intentions between partners. However, 44% of cycles with strong intentions to avoid pregnancy included intercourse on potentially fertile days or days of undetermined fertility status. Across all sensitivity scenarios, cumulative 13-cycle pregnancy rates with cycle intention to conceive ranged from 88.0% to 89.8%, and cumulative 13-cycle pregnancy rates with cycle intention to avoid ranged from 29.1% to 35.3%. In multivariate analysis, baseline motivations and intentions for pregnancy within 2 years were strongly correlated with the likelihood of pregnancy, more so than cycle intentions. The findings suggest that in some populations using natural family planning, baseline motivations and intentions may be more strongly related to pregnancy rates than cycle intentions. Our findings also highlight essential elements for evaluating correct use, including complete recording of intercourse and its timing.
Nutrition and Metabolic Health · Body Weight and Composition
Identifying atypical body mass index (BMI) trajectories in children and understanding associated, modifiable early-life factors may help prevent childhood obesity. To characterize multiphase BMI trajectories in children and identify associated modifiable early-life factors.Design, Setting, and ParticipantsThis cohort study included longitudinal data obtained from January 1997 to June 2024, from the Environmental influences on Child Health Outcomes (ECHO) cohort, which included children aged 1 to 9 years with 4 or more weight and height assessments. Analyses were conducted from January to June 2024. Exposure: sPrenatal exposure to substances and stress (smoking, alcohol, depression, anxiety), maternal characteristics (prepregnancy BMI, gestational weight gain), child characteristics (preterm birth, birth weight, breastfeeding), and demographic covariates.Main Outcomes and MeasuresBMI (calculated as weight in kilograms divided by length in meters squared for children aged 1 and 2 years and as weight in kilograms divided by height in meters squared for children older than 2 years) obtained using medical records, staff measurements, caregiver reports, or remote study measures. The analysis was conducted using a multiphase latent growth mixture model. This study included 9483 children (4925 boys [51.9%]). Two distinct 2-phase BMI patterns were identified: typical and atypical. The typical group (n = 8477 [89.4%]) showed linear decreases in BMI (b2, −0.23 [95% CI, −0.24 to −0.22]), with the lowest BMI at age 6 years (95% CI, 5.94-6.11), followed by linear increases from 6 to 9 years (slope difference [b4 − b2], 0.81 [95% CI, 0.76-0.86]; mean BMI at 9 years: 17.33). The atypical group (n = 1006 [10.6%]) showed a stable BMI from ages 1 to 3.5 years (b6, 0.06 [95% CI, −0.04 to 0.15]), followed by rapid linear increases from ages 3.5 to 9 years (slope difference [b8 − b6], 1.44 [95% CI, 1.34-1.55]). At age 9 years, this group reached a mean BMI (26.2) that exceeded the 99th percentile. Prenatal smoking, high prepregnancy BMI, high gestational weight gain, and high birth weight were key risk factors for the atypical trajectory. Conclusions and RelevanceIn this cohort study of children in the ECHO cohort, analyses identified children on the path to obesity as early as age 3.5 years. Modifiable factors could be targeted for early prevention and intervention programs aimed at reducing childhood obesity.
Fang R et al., 2025·Aerosol Air Qual. Res.·
Open Access
Background Low-cost sensors (LCS) are widely used for air quality monitoring, but their accuracy depends on proper calibration. This study compares linear regression (LR) and machine learning (ML) techniques, particularly random forest (RF), to determine optimal calibration strategies. Objectives This study aims to compare the effectiveness of LR and RF models in calibrating the Plantower PMS 3003 sensor under different environmental conditions. It also explores ways to streamline calibration efforts while maintaining accuracy. Methods Sensor data were collected in a controlled laboratory setting, with measurements compared against a reference monitor. LR and RF models were developed to calibrate the sensor, and their performance was evaluated based on RMSE, R2, and bias. Additionally, the study examined whether using fewer sensors for training could still produce reliable calibration models. Results Both LR and RF models demonstrated strong calibration performance. LR models were effective for low to moderate PM2.5 concentrations and required fewer computational resources, making them suitable for large-scale monitoring with limited resources. RF models captured nonlinear relationships, showing superior accuracy at high PM concentrations and in conditions with high relative humidity. The findings suggest that LR models trained on smaller datasets can achieve practical accuracy, reducing the need for extensive individual sensor calibration. Conclusions The selection of a calibration model should be guided by study-specific requirements, including environmental conditions and resource availability. LR models are recommended for large-scale studies with constrained resources, while RF models may offer advantages in high-exposure environments due to their ability to model complex interactions. This study is the first to explore reducing sensor calibration efforts while maintaining accuracy, highlighting the potential for optimized strategies in resource-limited settings. Future research should validate these findings in real-world deployments to further refine calibration models for LCS applications. Graphical Abstract
Duane M et al., 2022·BMC Pregnancy Childbirth·
Open Access
Miscarriage is defined as spontaneous loss of pregnancy prior to 20 weeks gestation. With an estimated risk of 15% of clinically confirmed pregnancies ending in miscarriage, it is the most common adverse event in pregnancy. Woman's age is the primary risk factor for miscarriage, while medical conditions, including hormonal abnormalities, are also associated. Progesterone is essential for maintaining pregnancy. A short luteal phase may reflect inadequate levels of progesterone production, but it is unclear whether a short luteal phase correlates with an increase in the risk of miscarriage. Using a cohort study design, we conducted a secondary data analysis from four cohorts of couples who used a standardized protocol to track biomarkers of the female cycles. A short luteal phase was defined as less than 10 days, with < 11, < 9, and < 8 days as alternate definitions in sensitivity analyses. We included women who experienced a pregnancy with a known outcome, identified the length of the luteal phase in up to 3 cycles prior to conception and assessed the relationship with miscarriage using a modified Poisson regression analysis, adjusting for demographic characteristics, smoking, alcohol use and previous pregnancy history. In our sample of 252 women; the overall miscarriage rate was 18.7%. The adjusted incident risk ratio of miscarriage in women who had at least one short luteal phase < 10 days, compared to those who had none, was 1.01 (95% CI: 0.57, 1.80) Similar null risk was found when assessing alternative lengths of short luteal phase. Women who had short luteal phases < 10 days in all 3 cycles prior to the conception cycle had an incident risk ratio of 2.14 (95% CI: 0.7, 6.55). Our study found that a short luteal phase in the three cycles prior to conception was not associated with higher rates of miscarriage in an international cohort of women tracking their cycles, but our sample size was limited. Further research to determine if short luteal phases or luteal phase deficiency is associated with early pregnancy losses among preconception cohorts with daily tracking of cycle parameters, in addition to progesterone and human chorionic gonadotropin levels, is warranted. Additionally, future studies should include women with recurrent short luteal phases as a more likely risk factor than isolated short luteal phases.
Najmabadi S et al., 2022·Hum Reprod Open·
Open Access
Does sexual intercourse enhance the cycle fecundability in women without known subfertility? Sexual intercourse (regardless of timing during the cycle) was associated with cycle characteristics suggesting higher fecundability, including longer luteal phase, less premenstrual spotting and more than 2 days of cervical fluid with estrogen-stimulated qualities. Human females are spontaneous ovulators, experiencing an LH surge and ovulation cyclically, independent of copulation. Natural conception requires intercourse to occur during the fertile window of a woman's menstrual cycle, i.e. the 6-day interval ending on the day of ovulation. However, most women with normal fecundity do not ovulate on Day 14, thus the timing of the hypothetical fertile window varies within and between women. This variability is influenced by age and parity and other known or unknown elements. While the impact of sexual intercourse around the time of implantation on the probability of achieving a pregnancy has been discussed by some researchers, there are limited data regarding how sexual intercourse may influence ovulation occurrence and menstrual cycle characteristics in humans. This study is a pooled analysis of three cohorts of women, enrolled at Creighton Model FertilityCare centers in the USA and Canada: 'Creighton Model MultiCenter Fecundability Study' (CMFS: retrospective cohort, 1990-1996), 'Time to Pregnancy in Normal Fertility' (TTP: randomized trial, 2003-2006) and 'Creighton Model Effectiveness, Intentions, and Behaviors Assessment' (CEIBA: prospective cohort, 2009-2013). We evaluated cycle phase lengths, bleeding and cervical mucus patterns and estimated the fertile window in 2564 cycles of 530 women, followed for up to 1 year. Participants were US or Canadian women aged 18-40 and not pregnant, who were heterosexually active, without known subfertility and not taking exogenous hormones. Most of the women were intending to avoid pregnancy at the start of follow-up. Women recorded daily vaginal bleeding, mucus discharge and sexual intercourse using a standardized protocol and recording system for up to 1 year, yielding 2564 cycles available for analysis. The peak day of mucus discharge (generally the last day of cervical fluid with estrogen-stimulated qualities of being clear, stretchy or slippery) was used to identify the estimated day of ovulation, which we considered the last day of the follicular phase in ovulatory cycles. We used linear mixed models to assess continuous cycle parameters including cycle, menses and cycle phase lengths, and generalized linear models using Poisson regression with robust variance to assess dichotomous outcomes such as ovulatory function, short luteal phases and presence or absence of follicular or luteal bleeding. Cycles were stratified by the presence or absence of any sexual intercourse, while adjusting for women's parity, age, recent oral contraceptive use and breast feeding. MAIN Most women were <30 years of age (75.5%; median 27, interquartile range 24-29), non-Hispanic white (88.1%), with high socioeconomic indicators and nulliparous (70.9%). Cycles with no sexual intercourse compared to cycles with at least 1 day of sexual intercourse were shorter (29.1 days (95% CI 27.6, 30.7) versus 30.1 days (95% CI 28.7, 31.4)), had shorter luteal phases (10.8 days (95% CI 10.2, 11.5) versus 11.4 days (95% CI 10.9, 12.0)), had a higher probability of luteal phase deficiency (<10 days; adjusted probability ratio (PR) 1.31 (95% CI 1.00, 1.71)), had a higher probability of 2 days of premenstrual spotting (adjusted PR 2.15 (95% CI 1.09, 4.24)) and a higher probability of having two or fewer days of peak-type (estrogenic) cervical fluid (adjusted PR 1.49 (95% CI 1.03, 2.15)). LIMITATIONS Our study participants were geographically dispersed but relatively homogeneous in regard to race, ethnicity, income and educational levels, and all had male partners, which may limit the generalizability of the findings. We cannot exclude the possibility of undetected subfertility or related gynecologic disorders among some of the women, such as undetected endometriosis or polycystic ovary syndrome, which would impact the generalizability of our findings. Acute illness or stressful events might have reduced the likelihood of any intercourse during a cycle, while also altering cycle characteristics. Some cycles in the no intercourse group may have actually had undocumented intercourse or other sexual activity, but this would bias our results toward the null. The Creighton Model FertilityCare System (CrM) discourages use of barrier methods, so we believe that most instances of intercourse involved exposure to semen; however, condoms may have been used in some cycles. Our dataset lacks any information about the occurrence of female orgasm, precluding our ability to evaluate the independent or combined impact of female orgasm on cycle characteristics. Sexual activity may change reproductive hormonal patterns, and/or levels of reproductive hormones may influence the likelihood of sexual activity. Future work may help with understanding the extent to which exposure to seminal fluid, and/or female orgasm and/or timing of intercourse could impact menstrual cycle function. In theory, large data sets from women using menstrual and fertility tracking apps could be informative if women can be appropriately incentivized to record intercourse completely. It is also of interest to understand how cycle characteristics may differ in women with gynecological problems or subfertility. Funding for the research on the three cohorts analyzed in this study was provided by the Robert Wood Johnson Foundation #029258 (Creighton Model MultiCenter Fecundability Study), the Eunice Kennedy Shriver National Institute of Child Health and Human Development 1K23 HD0147901-01A1 (Time to Pregnancy in Normal Fertility) and the Office of Family Planning, Office of Population Affairs, Health and Human Services 1FPRPA006035 (Creighton Model Effectiveness, Intentions, and Behaviors Assessment). The authors declare that they have no conflict of interest. N/A.
Duane M et al., 2022·Front Med (Lausanne)·
Open Access
Fertility awareness-based methods (FABMs) educate about reproductive health and enable tracking and interpretation of physical signs, such as cervical fluid secretions and basal body temperature, which reflect the hormonal changes women experience on a cyclical basis during the years of ovarian activity. Some methods measure relevant hormone levels directly. Most FABMs allow women to identify ovulation and track this "vital sign" of the menstrual or female reproductive cycle, through daily observations recorded on cycle charts (paper or electronic). Physicians can use the information from FABM charts to guide the diagnosis and management of medical conditions and to support or restore healthy function of the reproductive and endocrine systems, using a restorative reproductive medical (RRM) approach. FABMs can also be used by couples to achieve or avoid pregnancy and may be most effective when taught by a trained instructor. Information about individual FABMs is rarely provided in medical education. Outdated information is widespread both in training programs and in the public sphere. Obtaining accurate information about FABMs is further complicated by the numerous period tracking or fertility apps available, because very few of these apps have evidence to support their effectiveness for identifying the fertile window, for achieving or preventing pregnancy. This article provides an overview of different types of FABMs with a published evidence base, apps and resources for learning and using FABMs, the role FABMs can play in medical evaluation and management, and the effectiveness of FABMs for family planning, both to achieve or to avoid pregnancy.
Sanders JN et al., 2022·Reprod Health·
Open Access
In vitro fertilization (IVF) births contribute to a considerable proportion of preterm birth (PTB) each year. However, there is no formal surveillance of adverse perinatal outcomes for less invasive fertility treatments. The study objective was to describe associations between fertility treatment (in vitro fertilization, intrauterine insemination, usually with ovulation drugs (IUI), or ovulation drugs alone) and preterm birth, compared to no treatment in subfertile women. The Fertility Experiences Study (FES) is a retrospective cohort study conducted at the University of Utah between April 2010 and September 2012. Women with a history of primary subfertility self-reported treatment data via survey and interviews. Participant data were linked to birth certificates and fetal death records to asses for perinatal outcomes, particularly preterm birth. A total 487 birth certificates and 3 fetal death records were linked as first births for study participants who completed questionnaires. Among linked births, 19% had a PTB. After adjustment for maternal age, paternal age, maternal education, annual income, religious affiliation, female or male fertility diagnosis, and duration of subfertility, the odds ratios and 95% confidence intervals (CI) for PTB were 2.17 (CI 0.99, 4.75) for births conceived using ovulation drugs, 3.17 (CI 1.4, 7.19) for neonates conceived using IUI and 4.24 (CI 2.05, 8.77) for neonates conceived by IVF, compared to women with subfertility who used no treatment during the month of conception. A reported diagnosis of female factor infertility increased the adjusted odds of having a PTB 2.99 (CI 1.5, 5.97). Duration of pregnancy attempt was not independently associated with PTB. In restricting analyses to singleton gestation, odds ratios were not significant for any type of treatment. IVF, IUI, and ovulation drugs were all associated with a higher incidence of preterm birth and low birth weight, predominantly related to multiple gestation births.
What is the normal range of cervical mucus patterns and number of days with high or moderate day-specific probability of pregnancy (if intercourse occurs on a specific day) based on cervical mucus secretion, in women without known subfertility, and how are these patterns related to parity and age? The mean days of peak type (estrogenic) mucus per cycle was 6.4, the mean number of potentially fertile days was 12.1; parous versus nulliparous, and younger nulliparous (<30 years) versus older nulliparous women had more days of peak type mucus, and more potentially fertile days in each cycle. The rise in estrogen prior to ovulation supports the secretion of increasing quantity and estrogenic quality of cervical mucus, and the subsequent rise in progesterone after ovulation causes an abrupt decrease in mucus secretion. Cervical mucus secretion on each day correlates highly with the probability of pregnancy if intercourse occurs on that day, and overall cervical mucus quality for the cycle correlates with cycle fecundability. No prior studies have described parity and age jointly in relation to cervical mucus patterns. STUDY DESIGN, SIZE, This study is a secondary data analysis, combining data from three cohorts of women: 'Creighton Model MultiCenter Fecundability Study' (CMFS: retrospective cohort, 1990-1996), 'Time to Pregnancy in Normal Fertility' (TTP: randomized trial, 2003-2006), and 'Creighton Model Effectiveness, Intentions, and Behaviors Assessment' (CEIBA: prospective cohort, 2009-2013). We evaluated cervical mucus patterns and estimated fertile window in 2488 ovulatory cycles of 528 women, followed for up to 1 year. PARTICIPANTS/MATERIALS, SETTING, Participants were US or Canadian women age 18-40 years, not pregnant, and without any known subfertility. Women were trained to use a standardized protocol (the Creighton Model) for daily vulvar observation, description, and recording of cervical mucus. The mucus peak day (the last day of estrogenic quality mucus) was used as the estimated day of ovulation. We conducted dichotomous stratified analyses for cervical mucus patterns by age, parity, race, recent oral contraceptive use (within 60 days), partial breast feeding, alcohol, and smoking. Focusing on the clinical characteristics most correlated to cervical mucus patterns, linear mixed models were used to assess continuous cervical mucus parameters and generalized linear models using Poisson regression with robust variance were used to assess dichotomous outcomes, stratifying by women's parity and age, while adjusting for recent oral contraceptive use and breast feeding. MAIN The majority of women were <30 years of age (75.4%) (median 27; IQR 24-29), non-Hispanic white (88.1%), with high socioeconomic indicators, and nulliparous (70.8%). The mean (SD) days of estrogenic (peak type) mucus per cycle (a conservative indicator of the fertile window) was 6.4 (4.2) days (median 6; IQR 4-8). The mean (SD) number of any potentially fertile days (a broader clinical indicator of the fertile window) was 12.1 (5.4) days (median 11; IQR 9-14). Taking into account recent oral contraceptive use and breastfeeding, nulliparous women age ≥30 years compared to nulliparous women age <30 years had fewer mean days of peak type mucus per cycle (5.3 versus 6.4 days, P = 0.02), and fewer potentially fertile days (11.8 versus 13.9 days, P < 0.01). Compared to nulliparous women age <30 years, the likelihood of cycles with peak type mucus ≤2 days, potentially fertile days ≤9, and cervical mucus cycle score (for estrogenic quality of mucus) ≤5.0 were significantly higher among nulliparous women age ≥30 years, 1.90 (95% confidence interval (CI) 1.18, 3.06); 1.46 (95% CI 1.12, 1.91); and 1.45 (95% CI 1.03, 2.05), respectively. Between parous women, there was little difference in mucus parameters by age. Thresholds set a priori for within-woman variability of cervical mucus parameters by cycle were examined as follows: most minus fewest days of peak type mucus >3 days (exceeded by 72% of women), most minus fewest days of non-peak type mucus >4 days (exceeded by 54% of women), greatest minus least cervical mucus cycle score >4.0 (exceeded by 73% of women), and most minus fewest potentially fertile days >8 days (found in 50% of women). Race did not have any association with cervical mucus parameters. Recent oral contraceptive use was associated with reduced cervical mucus cycle score and partial breast feeding was associated with a higher number of days of mucus (both peak type and non-peak type), consistent with prior research. Among the women for whom data were available (CEIBA and TTP), alcohol and tobacco use had minimal impact on cervical mucus parameters. LIMITATIONS, We did not have data on some factors that may impact ovulation, hormone levels, and mucus secretion, such as physical activity and body mass index. We cannot exclude the possibility that some women had unknown subfertility or undiagnosed gynecologic disorders. Only 27 women were age 35 or older. Our study participants were geographically dispersed but relatively homogeneous with regard to race, ethnicity, income, and educational level, which may limit the generalizability of the findings. Patterns of cervical mucus secretion observed by women are an indicator of fecundity and the fertile window that are consistent with the known associations of age and parity with fecundity. The number of potentially fertile days (12 days) is likely greater than commonly assumed, while the number of days of highly estrogenic mucus (and higher probability of pregnancy) correlates with prior identifications of the fertile window (6 days). There may be substantial variability in fecundability between cycles for the same woman. Future work can use cervical mucus secretion as an indicator of fecundity and should investigate the distribution of similar cycle parameters in women with various reproductive or gynecologic pathologies. STUDY FUNDING/COMPETING INTEREST(S): Funding for the three cohorts analyzed was provided by the Robert Wood Johnson Foundation (CMFS), the Eunice Kennedy Shriver National Institute of Child Health and Human Development (TTP), and the Office of Family Planning, Office of Population Affairs, Health and Human Services (CEIBA). The authors declare that they have no conflict of interest. N/A.
Breast cancer is the leading cause of cancer death among Hispanic women. The aim of our study was to estimate cardiovascular disease (CVD) risk among Hispanic and non-Hispanic White (NHW) breast cancer survivors compared with their respective general population cohorts. Cohorts of 17 469 breast cancer survivors (1774 Hispanic and 15 695 NHW) in the Utah Cancer Registry diagnosed between 1997 and 2016, and 65 866 women (6209 Hispanic and 59 657 NHW) from the general population in the Utah Population Database were identified. Cox proportional hazards models were used to estimate hazard ratios (HRs) for CVD. The risk of diseases of the circulatory system was higher in Hispanic than NHW breast cancer survivors 1-5 years after cancer diagnosis, in comparison with their respective general population cohorts (HR(Hispanic) = 1.94, 99% confidence interval [CI] = 1.49 to 2.53; H(NHW) = 1.38, 99% CI = 1.33 to 1.43; 2-sided P (heterogeneity) = .01, respectively). Increased risks were observed for both Hispanic and NHW breast cancer survivors for diseases of the heart and the veins and lymphatics, compared with the general population cohorts. More than 5 years after cancer diagnosis, elevated risk of diseases of the veins and lymphatics persisted in both ethnicities. The CVD risk due to chemotherapy and hormone therapy was higher in Hispanic than NHW breast cancer survivors but did not differ for distant stage, higher baseline comorbidities, or baseline smoking. We observed a risk difference for diseases of the circulatory system between Hispanic and NHW breast cancer survivors compared with their respective general population cohorts but only within the first 5 years of cancer diagnosis.
While genitourinary complications during treatment for ovarian cancer are well-known, long-term adverse outcomes have not been well characterized. The number of ovarian cancer survivors has been increasing. The aim of this study was to investigate long-term adverse genitourinary outcomes in a population-based cohort. We identified a cohort of 1270 ovarian cancer survivors diagnosed between 1996 and 2012 from the Utah Cancer Registry, and 5286 cancer-free women were matched on birth year and state from the Utah Population Database. Genitourinary disease diagnoses were identified through ICD-9 codes from electronic medical records and statewide healthcare facilities data. Cox proportional hazards models were used to estimate hazard ratios (HR) for genitourinary outcomes at 1 to <5 years and 5+ years after ovarian cancer diagnosis. Ovarian cancer survivors had increased risks for urinary system disorders (HR: 2.53, 95% CI: 2.12-3.01) and genital organ disorders (HR: 1.88, 95% CI: 1.57-2.27) between 1 and <5 years after cancer diagnosis compared to the general population cohort. Increased risks were observed for acute renal failure, chronic kidney disease, calculus of kidney, hydronephrosis, pelvic peritoneal adhesions, and pelvic organ inflammatory conditions. Increased risks of several of these diseases were observed 5+ years after cancer diagnosis. Ovarian cancer survivors experience increased risks of various genitourinary diseases compared to women in the general population in the long-term. Understanding the multimorbidity trajectory among ovarian cancer survivors is important to improve clinical care after cancer treatment is completed.
Najmabadi S et al., 2020·Paediatr Perinat Epidemiol·
There is variability between women for days of menstrual bleeding, cycle lengths, follicular phase lengths, and luteal phase lengths, related to age and parity. To describe total cycle length; anovulatory cycles; follicular and luteal phase lengths; and days and intensity of menstrual and non-menstrual bleeding in women without known subfertility over the course of 1 year. 581 women (3,324 cycles) with no known subfertility (18-40 years of age) were followed for up to 1 year. Women recorded vaginal bleeding and mucus discharge daily. We used the peak day of cervical mucus as the estimated day of ovulation and the last day of the follicular phase. We used generalised linear mixed models stratified by age and parity to describe menstrual cycle parameters. The majority of women were <30 years of age (74.5%), non-Hispanic White (88.6%), and nulliparous (70.4%). The mean menses length was 6.2 (1.5) days, median 6; cycle length 30.3 (6.7) days, median 29; follicular phase length 18.5 (6.5) days, median 17; and luteal phase length 11.7 (2.8) days, median 12. Nulliparous women aged ≥30 years vs nulliparous women aged <30 had shorter cycles (29.2 days, 95% confidence interval (CI) 27.8, 30.7 vs 31.5 days, 95% CI 30.8, 32.2) and shorter follicular phases (17.6 days, 95% CI 16.2, 18.9 vs 19.6 days, 95% CI 18.9, 20.2). Among all women, within-woman differences between the longest and shortest menses length >3 days, total cycle length >7 days, follicular phase >7 days, and luteal phase >3 days were found in 11.6%, 43.0%, 41.7%, and 58.8% of women, respectively. Our findings confirm variability between women of menstrual cycle parameters related to age and parity, and also highlight within-woman variability in the follicular and luteal phases.
Previous research has demonstrated that women instructed in fertility awareness methods can identify the Peak Day of cervical mucus discharge for each menstrual cycle, and the Peak Day has high agreement with other indicators of the day of ovulation. However, previous studies enrolled experienced users of fertility awareness methods or were not fully blinded. To assess the agreement between cervical mucus Peak Day identified by fertile women without prior experience on assessing cervical mucus discharge with the estimated day of ovulation (1 day after urine luteinising hormone surge). This study is a secondary analysis of data from a randomised trial of the Creighton Model FertilityCare(TM) System (CrM), conducted 2003-2006, for women trying to conceive. Women who had no prior experience tracking cervical mucus recorded vulvar observations daily using a standardised assessment of mucus characteristics for up to seven menstrual cycles. Four approaches were used to identify the Peak Day. The referent day was defined as one day after the first identified day of luteinising hormone (LH) surge in the urine, assessed blindly. The percentage of agreement between the Peak Day and the referent day of ovulation was calculated. Fifty-seven women with 187 complete cycles were included. A Peak Day was identified in 117 (63%) cycles by women, 185 (99%) cycles by experts, and 187 (100%) by computer algorithm. The woman-picked Peak Day was the same as the referent day in 25% of 117 cycles, within ±1 day in 58% of cycles, ±2 days in 84%, ±3 days in 87%, and ±4 days in 92%. The ±1 day and ± 4 days' agreement was 50% and 90% for the expert-picked and 47% and 87% for the computer-picked Peak Day, respectively. Women's daily tracking of cervical mucus is a low-cost alternative for identifying the estimated day of ovulation.
Harville EW et al., 2019·Paediatr Perinat Epidemiol·
Open Access
Preconception health may have intergenerational influences. We have formed the PrePARED (Preconception Period Analysis of Risks and Exposures influencing health and Development) research consortium to address methodological, conceptual, and generalisability gaps in the literature. The consortium will investigate the effects of preconception exposures on four sets of outcomes: (1) fertility and miscarriage; (2) pregnancy-related conditions; (3) perinatal and child health; and (4) adult health outcomes. A study is eligible if it has data measured for at least one preconception time point, has a minimum of selected core data, and is open to collaboration and data harmonisation. The included studies are a mix of studies following women or couples intending to conceive, general-health cohorts that cover the reproductive years, and pregnancy/child cohort studies that have been linked with preconception data. The majority of the participating studies are prospective cohorts, but a few are clinical trials or record linkages. Data analysis will begin with harmonisation of data collected across cohorts. Initial areas of interest include nutrition and obesity; tobacco, marijuana, and other substance use; and cardiovascular risk factors. Twenty-three cohorts with data on almost 200 000 women have combined to form this consortium, begun in 2018. Twelve studies are of women or couples actively planning pregnancy, and six are general-population cohorts that cover the reproductive years; the remainder have some other design. The primary focus for four was cardiovascular health, eight was fertility, one was environmental exposures, three was child health, and the remainder general women's health. Among other cohorts assessed for inclusion, the most common reason for ineligibility was lack of prospectively collected preconception data. The consortium will serve as a resource for research in many subject areas related to preconception health, with implications for science, practice, and policy.
Prior studies among women with impaired fecundity have consistently demonstrated a positive association between daily perceived stress and the ability to conceive. However, the effects of daily stress on time to pregnancy (TTP) among women with proven fertility is not known. One hundred and forty-three women ages 18-35, in a relationship of proven fertility, who desired to conceive were included in the analysis. Daily diaries recording perceived stress (scale 0-10) were completed for up to 7 menstrual cycles or until pregnancy. Cox proportional hazards regression models were used to estimate the association between time-varying perceived stress tertiles (high [>4.1-7.2], moderate [>2.7-4.1], and low [0.1-2.7]) and adjusted fecundability odds ratio (aFOR), 95% confidence intervals (CI), after taking into account age, parity, education, time-varying caffeine and alcohol intake, fertility awareness tracking, and cycle intent to conceive. Among the 111 participants who completed daily diaries, 90 (81.1%) conceived. Women reporting high or moderate stress, versus low stress, had no difference in probability of achieving pregnancy (aFOR: 1.11 [95% CI: 0.58, 2.14]; and aFOR: 1.37 [0.71, 2.67]), respectively. Additional adjustment for intercourse frequency during narrow fertile window, or narrowing exposure focus to pre-ovulatory or pre-implantation stress did not appreciably alter the estimates. Daily perceived stress was not adversely associated with TTP among women with proven fertility. While a growing body of evidence supports adverse effects of more severe stressful life events on female reproductive function, moderate psychological stress, commonly referred to as eustress, among relatively healthy women with proven fertility does not appear to adversely impact TTP.
Bisphenol A (BPA) is a non-persistent endocrine-disrupting chemical with nearly ubiquitous, involuntary exposure. Previous studies have shown that BPA causes reproductive dysfunction in animal models, but there are limited data regarding the effects of BPA exposure on time to pregnancy (TTP) in humans. To evaluate whether peri-conceptional BPA exposure of women and men is associated with couples' TTP. A total of 164 heterosexual couples (164 women; 163 men) who have available BPA information as well as time to pregnancy from the Home Observation of Peri-conceptional Exposures (HOPE) Study were included and were followed up to 12 months. Women collected first-morning urine samples starting at the beginning of the fertile window and continued until the onset of menses or 18 days after the estimated day of ovulation (EDO+18 days). The time to pregnancy (TTP) after the enrolment was self-reported and used for the analysis. Discrete-time Cox proportional hazards models were performed to generate fecundability odds ratio (FOR) between BPA and TTP after adjusting for education and age, accounting for right censoring and prior number of cycles trying to conceive. Among 164 couples, 125 couples became pregnant during the study. There was no association between TTP and peri-conceptional BPA exposure for both men (FOR 1.02, 95% CI 0.72, 1.47) and women (FOR 1.07, 95% CI 0.75, 1.53) after adjusting for education and age. No association was found between peri-conceptional BPA exposure and fecundability in this preconception cohort of relatively young, healthy pregnancy planners.
Porucznik CA et al., 2017·Front Med (Lausanne)·
Open Access
The Creighton Model FertilityCare(TM) System (CrM) is a standardized approach for educating women about the biomarkers of their fertility. Couples can use this information for timing intercourse during "fertile" or "infertile" days in order to try to conceive or to avoid pregnancy. The study of Creighton Model Effectiveness, Intentions, and Behaviors Assessment (CEIBA) was conducted to assess fertility motivations, intentions, fertility-related sexual behaviors, and their impact on effectiveness to avoid and to conceive among new users of the CrM. This paper reports enrollment baseline characteristics. We conducted this prospective cohort study at 17 CrM FertilityCare(TM) Centers; 16 in the USA and one in Toronto, Canada. Couples who were new or returning users of the CrM were eligible. Couples who were initially trying to conceive or had a history of subfertility were excluded. Couples were enrolled and followed prospectively by their CrM instructors and also by CEIBA study staff. They completed baseline questionnaires. 1,132 new couples were assessed; 1,090 (96%) couples were screened; 429 (39%) couples were eligible; 305 women (71%) and 290 (95%) male partners were enrolled. The majority of women was engaged (39%) or married (51%), college graduates (77%), Caucasian non-Hispanic (80%), and Roman Catholic (80%). The most common reasons for learning CrM (women) were to use a natural method for family planning (91%), for moral/ethical/religious reasons (70%), the lack of side effects (71%), or insight into the menstrual cycle and fertility (62%). Women and men intended to have a mean of three and two additional children, respectively. Of women, 21% intended to have a child within a year and 60% between 1 and 3 years. The mean positive childbearing motivation score was 3.3 for both women and men (range 1-4, with 4 being most positive). Couples beginning use of the CrM to avoid pregnancy have high levels of motivation, desire, and intention for future childbearing. The CEIBA study has prospective measures of desires, intentions, and sexual/fertility behaviors for up to 1 year. We will assess the impact of desires, intentions, and behaviors on the pregnancy rates among these couples.
Porucznik CA et al., 2016·Environ Health·
Open Access
To examine transient environmental exposures and their relationship with human fecundity, exposure assessment should occur optimally at the time of conception in both members of the couple. We performed an observational, prospective cohort study with biomonitoring in both members of a heterosexual couple trying to conceive. Couples collected urine, saliva, and semen specimens for up to two menstrual cycles on days corresponding to the time windows of fertilization, implantation, and early pregnancy, identified based on the woman's observations of her cervical fluid. Three hundred nine eligible couples were screened between 2011 and 2015, of which 183 enrolled. Eleven couples (6.0 %) withdrew or were lost to follow up. The most successful and cost effective recruiting strategies were word of mouth (40 % of participating couples), posters and flyers (37 %), and targeted Facebook advertising (13 %) with an overall investment of $37.35 spent on recruitment per couple. Both men and women collected ≥97.2 % of requested saliva samples, and men collected ≥89.9 % of requested semen samples. Within the periovulatory days (±3 days), there was at least one urine specimen collected by women in 97.1 % of cycles, and at least one by men in 91.7 % of cycles. Daily compliance with periovulatory urine specimens ranged from 66.5 to 92.4 % for women and from 55.7 to 75.0 % for men. Compliance was ≥88 % for questionnaire completion at specified time points. Couples planning to conceive can be recruited successfully for periconceptional monitoring, and will comply with intensive study protocols involving home collection of biospecimens and questionnaire data.
Male Endocrine and Genetic Factors · Genetic Causes of Male Infertility
Jenkins TG et al., 2016·Fertil Steril·
Open Access
To evaluate the relationship between epigenetic patterns in sperm and fecundity.
Prospective study.
Academic andrology and in vitro fertilization laboratory. PATIENT(S): Twenty-seven semen samples from couples who conceived within 2 months of attempting a pregnancy and 29 semen samples from couples unable to achieve a pregnancy within 12 months. INTERVENTION(S): None. MAIN OUTCOME MEASURE(S): Genomewide assessment of differential sperm DNA methylation and standard semen analysis. RESULT(S): We analyzed DNA methylation alterations associated with fecundity in 124 semen samples, and identified regions of interest in 27 semen samples from couples who conceived within 2 months of attempting a pregnancy and a total of 29 semen samples from couples who were unable to achieve a pregnancy within 12 months. No differences in sperm count, sperm morphology, or semen volume were observed between the patients achieving a pregnancy within 2 months of study time and those not obtaining a pregnancy within 12 months. However, using data from the human methylation 450k array analysis we did identify two genomic regions with statistically significantly decreased (false discovery rate <0.01) methylation and three genomic regions with statistically significantly increased methylation in the failure-to-conceive group. The only two sites where decreased methylation was associated with reduced fecundity are at closely related genes known to be expressed in sperm, HSPA1L and HSPA1B. CONCLUSION(S): Our data suggest that there are genomic loci where DNA methylation alterations are associated with decreased fecundity. We have thus identified candidate loci for future study to verify these results and investigate the causative or contributory relationship between altered sperm methylation and decreased fecundity.
Measurement and Statistics · Instrument Development and Validation
Many women throughout the world have history of subfertility (resolved or unresolved), but much remains unknown about services and treatments chosen. We developed a mixed-mode fertility experiences questionnaire (FEQ) in 2009 through literature review and iterative pilot work to optimize question format and mode of administration. The focus of the FEQ is to collect data retrospectively on time at risk for pregnancy, fertility treatments received and declined, pregnancy, time to pregnancy and pregnancy outcomes. We conducted a validation of key elements of the FEQ with comparison to medical records in 2009 and 2010. The validation sample was selected from women initially seen at a specialized fertility treatment center in Utah in 2004. The FEQ was optimized with two components: 1) written (paper or web-based), self-administered, followed by 2) telephoneadministered questions. In 63 patients analyzed, high levels of correlation were identified between patient self-report and medical records for the use of intrauterine insemination and assisted reproductive technology, pregnancy and live birth histories, time at risk for pregnancy and time to pregnancy. There was low correlation between medical records and self-report for the use of oral ovulation drugs and injectable ovulation drugs. Compared to the medical record, the FEQ was over 90% sensitive for all elements, except injectable ovulation drugs (70% sensitivity). The FEQ accurately captured elements of fertility treatment history at 5-6 years after the first visit to a specialty clinic.
Schliep KC et al., 2015·Fertil Steril·
Open Access
To assess the effects of both male and female body mass index (BMI), individually and combined, on IVF outcomes.
Prospective cohort study.
University fertility center. PATIENT(S): All couples undergoing first fresh IVF cycles, 2005-2010, for whom male and female weight and height information were available (n = 721 couples). INTERVENTION(S): None. MAIN OUTCOME MEASURE(S): Embryologic parameters, clinical pregnancy, and live birth incidence. RESULT(S): The average male BMI among the study population was 27.5 ± 4.8 kg/m(2) (range, 17.3-49.3 kg/m(2)), while the average female BMI (n = 721) was 25.2 ± 5.9 kg/m(2) (range, 16.2-50.7 kg/m(2)). Neither male nor female overweight (25-29.9 kg/m(2)), class I obese (30-34.9 kg/m(2)), or class II/III obese (≥35 kg/m(2)) status was significantly associated with fertilization rate, embryo score, or incidence of pregnancy or live birth compared with normal weight (18.5-24.9 kg/m(2)) status after adjusting for male and female age, partner BMI, and parity. Similar null findings were found between combined couple BMI categories and IVF success. CONCLUSION(S): Our findings support the notion that weight status does not influence fecundity among couples undergoing infertility treatment. Given the limited and conflicting research on BMI and pregnancy success among IVF couples, further research augmented to include other adiposity measures is needed.
Porucznik CA et al., 2014·BMC Womens Health·
Open Access
Transient exposures may influence fertility and early embryonic development. To assess the time of conception in vivo and conduct concurrent biomonitoring, ovulation must be identified prospectively. We report on the development and validation of a simple, prospective method, the Peak Day method, to determine likely day of ovulation based upon daily observations of cervical fluid. We recruited 98 women to learn the Peak Day method from a brochure, 26 of whom concurrently used the method with blinded daily urine hormone monitoring (estrone glucuronide and luteinizing hormone). All women were instructed to complete an exposure questionnaire immediately upon identifying ovulation. Briefly, the exposure questionnaire captured time-varying and transient exposures such as medication use, water consumption, and amount of sleep. We assessed timely completion of the exposure questionnaire, agreement of women's estimated day of ovulation (EDO) and the EDO by expert review, and agreement between the EDO by expert review and by blinded urine monitoring. Of 147 cycles evaluated, women selected an EDO in 130 (88%) and subsequently completed the periovulatory exposure questionnaire in 122 (94%) cycles. Of the 26 cycles evaluated with blinded hormonal monitoring, the Peak Day "best quality" algorithm, based upon cervical fluid, identified ovulation ± 3 days of the urine monitor in 24 cycles (92%). With simple written instructions, women can identify an estimated day of ovulation and perform periovulatory exposure assessment. The Peak Day method is highly cost-effective and could be applied by researchers to target periconceptional or very early developmental stage exposure assessment.
The purpose of this study was to compare the utilization of medical help for fertility among women who reported up to a year versus more than a year of trying to become pregnant and to describe the characteristics of those women seeking early treatment. Data from the 2004-2008 Pregnancy Risk Assessment Monitoring System (PRAMS) survey were used to assess attempt duration and use of fertility treatments in a sample of 9,517 women who had a recent live birth in Utah. PRAMS respondents who were trying to become pregnant at the time of conception were asked questions about fertility treatments (sampling n = 5,238; representative n = 153,036). Univariate and bivariate analyses were used to describe and compare characteristics of women who sought treatment after attempting pregnancy for a year or less and women who waited at least a year to seek treatment. Among women who were trying to become pregnant, 9.5 % reported using some medical assistance to conceive. Among the women trying to become pregnant, 89.3 % had been trying for ≤12 months and 10.7 % reported having tried >12 months. 5.2 % of those trying to become pregnant for up to a year reported use of fertility treatment, compared with 45.8 % of those trying for a year or more. Women who had previous live births were significantly more likely to use early treatment than nulliparous women (aOR = 2.4, 95 % CI = 1.5, 3.9). The use of fertility drugs and other treatments were more common than ART among recipients of early treatment (aOR = 3.7, 95 % CI = 1.7, 7.9). Some women may be receiving fertility treatment before it is clinically indicated. Instead of invasive treatment, these women may benefit from preconception counseling on folic acid, healthy prepregnancy weight and use of ovulation monitoring to time intercourse.