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Endometriosis is a debilitating, chronic disease that is estimated to affect 11% of reproductive-age women. Diagnosis of endometriosis is difficult with diagnostic delays of up to 12 years reported. These delays can negatively impact health and quality of life. Vague, nonspecific symptoms, like pain, with multiple differential diagnoses contribute to the difficulty of diagnosis. By investigating previously imprecise symptoms of pain, we sought to clarify distinct pain symptoms indicative of endometriosis, using an artificial intelligence-based approach. We used data from 473 women undergoing laparoscopy or laparotomy for a variety of surgical indications. Multiple anatomical pain locations were clustered based on the associations across samples to increase the power in the probability calculations. A Bayesian network was developed using pain-related features, subfertility, and diagnoses. Univariable and multivariable analyses were performed by querying the network for the relative risk of a postoperative diagnosis, given the presence of different symptoms. Performance and sensitivity analyses demonstrated the advantages of Bayesian network analysis over traditional statistical techniques. Clustering grouped the 155 anatomical sites of pain into 15 pain locations. After pruning, the final Bayesian network included 18 nodes. The presence of any pain-related feature increased the relative risk of endometriosis (p-value < 0.001). The constellation of chronic pelvic pain, subfertility, and dyspareunia resulted in the greatest increase in the relative risk of endometriosis. The performance and sensitivity analyses demonstrated that the Bayesian network could identify and analyze more significant associations with endometriosis than traditional statistical techniques. Pelvic pain, frequently associated with endometriosis, is a common and vague symptom. Our Bayesian network for the study of pain-related features of endometriosis revealed specific pain locations and pain types that potentially forecast the diagnosis of endometriosis.

Purpose It is thought that total energy intake in women is increased during the luteal versus follicular phase of the menstrual cycle; however, less is understood regarding changes in diet composition (i.e., macro- and micronutrient intakes) across the cycle. The aim of this study was to investigate changes in macronutrient, micronutrient, and food group intakes across phases of the menstrual cycle among healthy women, and to assess whether these patterns differ by ovulatory status. Methods The BioCycle study (2005–2007) was a prospective cohort study of 259 healthy regularly menstruating women age 18–44 who were followed for up to two menstrual cycles. Dietary intake was measured using 24-h dietary recalls, and food cravings were assessed via questionnaire, up to four times per cycle, corresponding to menses, mid-follicular, expected ovulation, and luteal phases. Linear mixed models adjusting for total energy intake were used to evaluate changes across the cycle. Results Total protein ( P  = 0.03), animal protein ( P  = 0.05), and percent of caloric intake from protein ( P  = 0.02) were highest during the mid-luteal phase compared to the peri-ovulatory phase. There were also significant increases in appetite, craving for chocolate, craving for sweets in general, craving for salty flavor, and total craving score during the late luteal phase compared to the menstrual, follicular, and ovulatory phases ( P  < 0.001). Conclusions Our findings suggest an increased intake of protein, and specifically animal protein, as well as an increase in reported food cravings, during the luteal phase of the menstrual cycle independent of ovulatory status. These results highlight a plausible link between macronutrient intake and menstrual cycle phase.

Evolutionary theory suggests that some animal species may experience shifts in their offspring sex ratio in response to maternal health and environmental conditions, and in some unfavorable conditions, females may be less likely to bear sons. Experimental data in both animals and humans indicate that maternal inflammation may disproportionately impact the viability of male conceptuses; however, it is unknown whether other factors associated with both pregnancy and inflammation, such as vitamin D status, are associated with the offspring sex ratio. Here, we show that among 1,228 women attempting pregnancy, preconception 25-hydroxyvitamin D concentrations are positively associated with the live birth of a male infant, with notably stronger associations among women with elevated high sensitivity C-reactive protein, a marker of systemic low-grade inflammation. Our findings suggest that vitamin D may mitigate maternal inflammation that would otherwise be detrimental to the implantation or survival of male conceptuses in utero. Higher vitamin D is associated with improved pregnancy and live birth rates, but its potential role in the human offspring sex ratio in unknown. Here, the authors show that the levels of vitamin D at preconception are positively associated with male live birth, particularly among women presenting inflammatory markers.

Introduction Clinical notes, biomarkers, and neuroimaging have proven valuable in dementia prediction models. Whether commonly available structured clinical data can predict dementia is an emerging area of research. We aimed to predict gold-standard, research-based diagnoses of dementia including Alzheimer’s disease (AD) and/or Alzheimer’s disease related dementias (ADRD), in addition to ICD-based AD and/or ADRD diagnoses, in a well-phenotyped, population-based cohort using a machine learning approach. Methods Administrative healthcare data (k = 163 diagnostic features), in addition to census/vital record sociodemographic data (k = 6 features), were linked to the Cache County Study (CCS, 1995–2008). Results Among successfully linked UPDB-CCS participants ( n  = 4206), 522 (12.4%) had incident dementia (AD alone, AD comorbid with ADRD, or ADRD alone) as per the CCS “gold standard” assessments. Random Forest models, with a 1-year prediction window, achieved the best performance with an Area Under the Curve (AUC) of 0.67. Accuracy declined for dementia subtypes: AD/ADRD (AUC = 0.65); ADRD (AUC = 0.49). Accuracy improved when using ICD-based dementia diagnoses (AUC = 0.77). Discussion Commonly available structured clinical data (without labs, notes, or prescription information) demonstrate modest ability to predict “gold-standard” research-based AD/ADRD diagnoses, corroborated by prior research. Using ICD diagnostic codes to identify dementia as done in the majority of machine learning dementia prediction models, as compared to “gold-standard” dementia diagnoses, can result in higher accuracy, but whether these models are predicting true dementia warrants further research.

Background Prior research indicates that at least 35% of Alzheimer’s disease and related dementia risk may be amenable to prevention. Subjective cognitive decline is often the first indication of preclinical dementia, with the risk of subsequent Alzheimer’s disease in such individuals being greater in women than men. We wished to understand how modifiable factors are associated with subjective cognitive decline, and whether differences exist by sex. Methods Data were collected from men and women (45 years and older) who completed the U.S. Behavioral Risk Factor Surveillance System Cognitive Decline Module (2015–2018), n  = 216,838. We calculated population-attributable fractions for subjective cognitive decline, stratified by sex, of the following factors: limited education, deafness, social isolation, depression, smoking, physical inactivity, obesity, hypertension, and diabetes. Our models were adjusted for age, race, income, employment, marital and Veteran status, and accounted for communality among risk factors. Results The final study sample included more women (53.7%) than men, but both had a similar prevalence of subjective cognitive decline (10.6% of women versus 11.2% of men). Women and men had nearly equivalent overall population-attributable fractions to explain subjective cognitive decline (39.7% for women versus 41.3% for men). The top three contributing risk factors were social isolation, depression, and hypertension, which explained three-quarters of the overall population-attributable fraction. Conclusions While we did not identify any differences in modifiable factors between men and women contributing to subjective cognitive decline, other factors including reproductive or endocrinological health history or biological factors that interact with sex to modify risk warrant further research. Highlights Subjective Cognitive Decline (SCD) is one of the earliest noticeable symptoms of Alzheimer’s disease and related dementias. While there is no current cure for dementia, research indicates that at least 35% of dementia risk may be modifiable by decreasing exposures years or even decades before cognitive decline becomes clinically evident. Prior research has shown that the risk of dementia in individuals with cognitive impairment is higher in women than in men, as is the overall risk of dementia. Among a nationally representative population of over 200,000 adults, ages 45 years and older, SCD prevalence was 11% for both women and men. Women and men also had nearly equivalent overall population-attributable fractions to explain subjective cognitive decline (39.7% for women versus 41.3% for men). The top three contributing risk factors for both women and men were social isolation, depression, and hypertension, which explained three-quarters of the overall population-attributable fraction.

Introduction Women with hypertensive disorders of pregnancy (HDP) have an increased risk of cardiovascular disease. Whether HDP is also associated with later‐life dementia has not been fully explored. Methods Using the Utah Population Database, we performed an 80‐year retrospective cohort study of 59,668 parous women. Results Women with, versus without, HDP, had a 1.37 higher risk of all‐cause dementia (95% confidence interval [CI]: 1.26, 1.50) after adjustment for maternal age at index birth, birth year, and parity. HDP was associated with a 1.64 higher risk of vascular dementia (95% CI: 1.19, 2.26) and 1.49 higher risk of other dementia (95% CI: 1.34, 1.65) but not Alzheimer's disease dementia (adjusted hazard ratio = 1.04; 95% CI: 0.87, 1.24). Gestational hypertension and preeclampsia/eclampsia showed similar increased dementia risk. Nine mid‐life cardiometabolic and mental health conditions explained 61% of HDP's effect on subsequent dementia risk. Discussion Improved HDP and mid‐life care could reduce the risk of dementia.

Per- and polyfluoroalkyl substances (PFAS) exposure is widespread and has been linked with gynecologic disease. To our knowledge, no study has measured PFAS in endometrial tissue. Eutopic endometrial tissue specimens ( ) were collected from Investigating Mixtures of Pollutants and Endometriosis in Tissue (IMPLANT) study participants undergoing laparoscopy or laparotomy for any indication (2007-2009). Nine PFAS were measured by high-performance liquid chromatography-tandem mass spectrometry [perfluorodecanoic acid (PFDA), perfluorohexane sulfonic acid (PFHxS), perfluorononanoic acid (PFNA), perfluorooctanoic acid (PFOA), perfluorooctane sulfonic acid (PFOS), perfluorododecanoic acid (PFDoDA), perfluoroheptanoic acid (PFHpA), perfluorooctanesulfonamide (PFOSA), and perfluoroundecanoic acid (PFUnDA)]. Surgeons diagnosed endometriosis by gold-standard visualization and evaluated the endometriosis staging as moderate and severe (stages 3 and 4) compared to minimal and mild (stages 1 and 2) using American Society of Reproductive Medicine (ASRM) classification. We used modified Poisson regression models adjusted for age (continuous), race (white, all other race/ethnicities), smoking status (serum cotinine ), study site (Utah, California), and body mass index (continuous) to obtain relative risks (RR) of endometriosis diagnosis and 95% confidence intervals (CIs) for each PFAS. PFAS mixtures were evaluated using Bayesian kernel machine regression. Participants were, on average, years old, and 75% of participants were non-Hispanic white. Of the 181 participants with an incident endometriosis diagnosis, 73% had ASRM stage 1 or 2, while 27% had stage 3 or 4. Median [interquartile range (IQR)] eutopic endometrium tissue levels, in nanograms per gram, were 6.58 (6.44) for PFOS, 1.93 (1.71) for PFOA, 0.65 (0.75) for PFHxS, 0.58 (0.52) for PFNA, and 0.12 (0.18) for PFOSA. PFAS in the endometrial tissue was not associated with endometriosis. However, select PFAS in the eutopic tissue were associated with a risk of more advanced (stage 3 or 4 vs. 1 or 2) endometriosis [PFOSA (95% CI: 1.10, 1.43), PFHxS (95% CI: 1.12, 1.68), PFOS (95% CI: 1.02, 1.81)]. PFAS were widely detected in eutopic endometrial tissue. There was no evidence that PFAS in endometrial tissue were associated with a higher risk of endometriosis diagnosis. However, PFOS, PFOSA, and PFHxS in the endometrial tissue were associated with risk of more severe stage of endometriosis. https://doi.org/10.1289/EHP15852.

BACKGROUND: Per- and polyfluoroalkyl substances (PFAS) exposure is widespread and has been linked with gynecologic disease. To our knowledge, no study has measured PFAS in endometrial tissue. METHODS: Eutopic endometrial tissue specimens (n= 434) were collected from Investigating Mixtures of Pollutants and Endometriosis in Tissue (IMPLANT) study participants undergoing laparoscopy or laparotomy for any indication (2007-2009). Nine PFAS were measured by highperformance liquid chromatography--tandem mass spectrometry [perfluorodecanoic acid (PFDA), perfluorohexane sulfonic acid (PFHxS), perfluorononanoic acid (PFNA), perfluorooctanoic acid (PFOA), perfluorooctane sulfonic acid (PFOS), perfluorododecanoic acid (PFDoDA), perfluoroheptanoic acid (PFHpA), perfluorooctanesulfonamide (PFOSA), and perfluoroundecanoic acid (PFUnDA)]. Surgeons diagnosed endometriosis by gold-standard visualization and evaluated the endometriosis staging as moderate and severe (stages 3 and 4) compared to minimal and mild (stages 1 and 2) using American Society of Reproductive Medicine (ASRM) classification. We used modified Poisson regression models adjusted for age (continuous), race (white, all other race/ethnicities), smoking status (serum cotinine >10 ng/mL), study site (Utah, California), and body mass index (continuous) to obtain relative risks (RR) of endometriosis diagnosis and 95% confidence intervals (CIs) for each PFAS. PFAS mixtures were evaluated using Bayesian kernel machine regression. RESULTS: Participants were, on average, 33 [+ or -] 7 years old, and 75% of participants were non-Hispanic white. Of the 181 participants with an incident endometriosis diagnosis, 73% had ASRM stage 1 or 2, while 27% had stage 3 or 4. Median [interquartile range (IQR)] eutopic endometrium tissue levels, in nanograms per gram, were 6.58 (6.44) for PFOS, 1.93 (1.71) for PFOA, 0.65 (0.75) for PFHxS, 0.58 (0.52) for PFNA, and 0.12 (0.18) for PFOSA. PFAS in the endometrial tissue was not associated with endometriosis. However, select PFAS in the eutopic tissue were associated with a risk of more advanced (stage 3 or 4 vs. 1 or 2) endometriosis [PFOSA RR = 1:25 (95% CI: 1.10, 1.43), PFHxS RR = 1:37 (95% CI: 1.12, 1.68), PFOS RR = 1:36 (95% CI: 1.02, 1.81)]. CONCLUSION: PFAS were widely detected in eutopic endometrial tissue. There was no evidence that PFAS in endometrial tissue were associated with a higher risk of endometriosis diagnosis. However, PFOS, PFOSA, and PFHxS in the endometrial tissue were associated with risk of more severe stage of endometriosis.

BACKGROUND:Stress has been shown to suppress ovulation in experimental models, but its effect on human reproduction at the population level is unclear. METHODS:Healthy women (n = 259), aged 18–44 years from Western New York, were followed for 2 menstrual cycles (2005–2007). Women completed daily perceived stress assessments, a 4-item Perceived Stress Scale (PSS-4) up to 4 times each cycle, and a 14-item PSS at baseline. Mixed model analyses were used to assess effects of stress on log reproductive hormone concentrations and sporadic anovulation. RESULTS:High versus low daily stress was associated with lower estradiol (−9.5% [95% confidence interval (CI) = −15.6% to −3.0%]), free estradiol (−10.4% [−16.5% to −3.9%]), and luteinizing hormone (−14.8% [−21.3% to −7.7%]) and higher follicle-stimulating hormone (6.2% [95% CI = 2.0% to 10.5%]) after adjusting for age, race, percent body fat, depression score, and time-varying hormones and vigorous exercise. High versus low daily stress was also associated with lower luteal progesterone (−10.4% [95% CI = −19.7% to −0.10%]) and higher odds of anovulation (adjusted odds ratio = 2.2 [95% CI = 1.0 to 4.7]). For each unit increase in daily stress level, women had a 70% higher odds of an anovulatory episode (odds ratio = 1.7 [1.1 to 2.4]). Similar but attenuated results were found for the association between the PSS-4 and reproductive hormones, while null findings were found for the baseline PSS. CONCLUSION:Daily perceived stress does appear to interfere with menstrual cycle function among women with no known reproductive disorders, warranting further research to explore potential population-level impacts and causal biologic mechanisms.

Although minerals are linked to several reproductive outcomes, it is unknown whether dietary minerals are associated with ovulatory function. We hypothesised that low intakes of minerals would be associated with an increased risk of anovulation. We investigated associations between dietary mineral intake and both reproductive hormones and anovulation in healthy women in the BioCycle Study, which prospectively followed up 259 regularly menstruating women aged 18–44 years who were not taking mineral supplements for two menstrual cycles. Intakes of ten selected minerals were assessed through 24-h dietary recalls at up to four times per cycle in each participant. Oestradiol, progesterone, luteinising hormone (LH), follicle-stimulating hormone (FSH), sex-hormone-binding globulin and testosterone were measured in serum up to eight times per cycle. We used weighted linear mixed models to evaluate associations between minerals and hormones and generalised linear models for risk of anovulation. Compared with Na intake ≥1500 mg, Na intake <1500 mg was associated with higher levels of FSH (21·3 %; 95 % CI 7·5, 36·9) and LH (36·8 %; 95 % CI 16·5, 60·5) and lower levels of progesterone (−36·9 %; 95 % CI −56·5, −8·5). Na intake <1500 mg (risk ratio (RR) 2·70; 95 % CI 1·00, 7·31) and Mn intake <1·8 mg (RR 2·00; 95 % CI 1·02, 3·94) were associated with an increased risk of anovulation, compared with higher intakes, respectively. Other measured dietary minerals were not associated with ovulatory function. As essential minerals are mostly obtained via diet, our results comparing insufficient levels with sufficient levels highlight the need for future research on dietary nutrients and their associations with ovulatory cycles.