Janet Wilson Rich-Edwards

Context: Menstrual irregularities have been associated with cardiovascular disease (CVD) risk, but underlying etiologies may confer distinct risk profiles. Functional hypothalamic amenorrhea (FHA) has not been evaluated as a separate risk phenotype. Objective: To assess the association between FHA phenotype and incident CVD and cardiometabolic risk factors. Design: Prospective cohort study with biennial follow-up from 1993 to 2019. Setting: Nurses’ Health Study II cohort. Participants: The sample included 52 655 premenopausal women free of CVD in 1993. FHA phenotype was defined as irregular or absent cycles without polycystic ovary syndrome traits combined with low body mass index and/or high physical activity. Intervention: None. Main Outcome Measures: Incident CVD (coronary heart disease [CHD; myocardial infarction or coronary revascularization] and stroke) and incident elevated cholesterol, hypertension, and type 2 diabetes (T2DM). Results: During up to 26 years of follow-up, 1007 CVD events occurred. Among women who developed CVD, the median time to the first CVD event was 17.0 years (IQR, 11.3-21.0). FHA phenotype in mid-adulthood was associated with a 62% higher risk of CVD (95% CI: 1.01-2.59), driven by an almost 2-fold higher risk of CHD (hazard ratio [HR] = 1.91; 95% CI: 1.11-3.27), compared with women with regular cycles. FHA was also associated with T2DM (HR = 1.86; 95% CI: 1.41-2.47), but not hypertension or elevated cholesterol. Non-FHA menstrual irregularity was associated with elevated cholesterol, hypertension, and T2DM, but not CVD. FHA in early adulthood was not associated with outcomes. Conclusion: FHA phenotype in mid-adulthood was associated with increased CHD risk independent of traditional risk factors. Menstrual history may serve as an early marker of cardiometabolic risk.

BACKGROUND: Few studies have examined how multiple types of adverse pregnancy outcomes across women’s reproductive lives relate to long-term cardiovascular disease. METHODS: In 59 154 parous participants in Nurses’ Health Study II, lifetime history of gestational diabetes, gestational hypertension, preeclampsia, preterm delivery, and low birth weight was self-reported, and cardiovascular events, including myocardial infarction, stroke, and coronary revascularization, were identified through June 2017. We used Cox proportional hazards models to estimate associations between adverse pregnancy outcomes and cardiovascular disease and quantified the extent to which these associations were explained by the later development of hypertension, diabetes, and hypercholesterolemia. We evaluated whether adding adverse pregnancy outcomes improved prediction of premature cardiovascular disease beyond established risk factors such as systolic blood pressure and diabetes. RESULTS: Each adverse pregnancy outcome was associated with a higher risk of long-term cardiovascular disease. Only gestational hypertension (hazard ratio, 1.62 [95% CI, 1.36–1.92]) and preeclampsia (1.31 [1.11–1.55]) retained independent associations after accounting for the cooccurrence of other adverse pregnancy outcomes. Postpregnancy hypertension, diabetes, and hypercholesterolemia jointly accounted for substantial attenuation (58.4% [38.7%–75.8%]) of the association between adverse pregnancy outcomes in the first pregnancy and later cardiovascular disease. Adding adverse pregnancy outcomes only modestly improved discrimination and slightly improved reclassification. CONCLUSIONS: Common adverse pregnancy outcomes, especially gestational hypertension and preeclampsia, are associated with higher future cardiovascular risk, with much of this association attenuated after accounting for subsequent cardiovascular risk factors. However, given the limited predictive gains, more nuanced integration of adverse pregnancy outcomes is needed to enhance their clinical utility in cardiovascular risk prediction.

In 2016, the National Institutes of Health designated LGBTQ+ individuals (ie, lesbian, gay, bisexual, transgender, queer, and all sexual and gender minorities) as a health disparities population. The growing interest in studying the health of LGBTQ+ populations merits revisiting the methodological approaches researchers employ. We elucidate how researchers can identify appropriate adjustment sets for causal questions using directed acyclic graphs (DAGs). To illustrate these points, we simulated a simplified example using pregnancy loss as the outcome wherein we generate 1000 datasets with a sample size of 10 000 individuals. We motivate why covariates that are commonly used in LGBTQ+ health disparities research (eg, use of medically assisted reproduction) are mediators, not confounders, and how adjusting for these variables in causal research can induce bias by blocking part of the indirect effect of exposure on the outcome. Next, we illustrate the complexity of mediation analyses with social exposures due to mediator-outcome confounding induced by exposure and compare potential approaches. Then we demonstrate how collider stratification bias can arise from our sample recruitment and selection. Finally, we demonstrate how incorporating heterosexism (ie, stigma and discrimination) as an unobserved node in our DAG can guide decision-making on appropriate adjustment sets. This article is part of a Special Collection on Methods in Social Epidemiology.

Some families consistently have offspring of only one sex, raising questions about whether sex at birth is truly random. This study investigated whether offspring sex follows a simple binomial distribution within families and identified maternal factors associated with unisexual sibships. We analyzed 58,007 US women with two or more singleton live births (146,064 pregnancies, 1956–2015). Offspring sex followed a beta-binomial rather than a simple binomial distribution, indicating that each family may have a unique probability of male or female births, akin to a weighted coin toss. Deviations from simple binomial distribution were more pronounced when we excluded each woman’s last birth to reduce the influence of sex-based stopping behavior. After excluding the last birth, older maternal age at first birth was associated with higher odds of having offspring of only one sex. A genome-wide association study identified maternal SNPs linked to having female-only ( NSUN6 ) and male-only ( TSHZ1 ) offspring. Our findings suggest maternal factors influence offspring sex distributions.

Background: Burnout among health care workers affects their well-being and decision-making, influencing patient and public health outcomes. Health care workers’ health beliefs and COVID-19 vaccine decisions may affect the risks of burnout. Therefore, understanding the interplay between these crucial factors is essential for identifying at-risk staff, providing targeted support, and addressing workplace challenges to prevent further escalation of burnout-related issues. Objective: This study examines how burnout is impacted by health beliefs and COVID-19 vaccine decisions among health care workers. Building on our previously developed Health Belief Model (HBM) classifier based on the HBM framework, which explains how individual perceptions of health risks and benefits influence behavior, we focused on key HBM constructs, including the perceived severity of COVID-19, perceived barriers to vaccination, and their relationship to burnout. We aim to leverage natural language processing techniques to automatically identify theoretically grounded burnout symptoms from comments authored by nurses in a large-scale, national survey and assess their associations with vaccine hesitancy and health beliefs. Methods: We analyzed 1944 open-ended comments written by 1501 vaccine-hesitant nurses, using data from the Nurses’ Health Study surveys. We fine-tuned LLaMA 3, an open-source large language model with few-shot prompts and enhanced performance with structured annotation guidance and reasoning-aware inference. Comments were classified into burnout dimensions—Emotional Exhaustion, Depersonalization, and Inefficacy—based on the Maslach Burnout Inventory framework. Results: The model achieved a high weighted accuracy of 92% and an F₁-score of 91% for Depersonalization. Emotional Exhaustion was identified in 52% (1003/1944) of comments, correlating strongly with perceived severity (189/323, 59%) and barriers to vaccination (281/650, 43%). Demographic analyses revealed significant variations in burnout prevalence, with older age groups reporting greater burnout. Conclusions: This study highlights the relationship between burnout and vaccine decision-making among health care workers, uncovering areas for further exploration. By exploring the complex interplay between psychological strain and vaccine hesitancy, this study sets the stage for developing transformative interventions and policies that could redefine workforce resilience and public health strategies.

Aims: Despite well-studied associations between hypertensive disorders of pregnancy (HDP) and atrial fibrillation (AF), the mechanisms of the excess risk of AF in women with history of HDP are not fully understood. Furthermore, little is known about associations between other adverse pregnancy outcomes (APOs) and AF, including preterm birth, small/large-for-gestational-age (SGA/LGA) offspring. Methods and results: By linking the population-based HUNT study with the Medical Birth Registry of Norway (MBRN) and electronic patient administrative systems, 15 104 women ≥45 years with 34 674 births were followed and assessed for validated AF for a median of 12.9 years. Information on APOs was retrieved from the MBRN. We used Cox proportional hazards models to calculate hazard ratios (HRs) for associations of APOs with the risk of AF. By inverse odds ratio weighting, we assessed modifiable AF risk factors that could explain the associations. Among women aged 45–65, those with HDP had a higher risk of AF [HR 2.03, 95% confidence interval (CI) 1.27–3.24] as women without HDP, but not among women >65 years (HR 0.95, 95% CI 0.57–1.60). A history of LGA was associated with increased risk of AF (HR 1.38, 95% CI 1.03–1.84), but histories of preterm birth or SGA were not (HR 0.94, 95% CI 0.63–1.41, HR 0.90, 95% CI 0.66–1.23). Post-pregnancy body mass index might possibly explain ∼45% of the associations between HDP or LGA and AF. Conclusion: Women with history of HDP or LGA offspring are at higher risk of AF.

Background: At the beginning of the coronavirus disease (COVID-19) pandemic, healthcare personnel (HCP) faced a dire shortage of personal protective equipment (PPE). This shortage has been identified as a major source of distress among HCP during the early COVID-19 pandemic, though the specific consequences of this shortage have not been identified in the qualitative literature. Methods: We sought to fill this gap by conducting a qualitative analysis of PPE related free-text comments from online surveys completed by 923 HCP during Spring 2020. Results: We found that HCP used words such as “required” and “had” to describe how their use of non-standard PPE was imposed on them by their workplace, suggesting that they felt little control over their protection at work. HCP described cleaning PPE with novel methods, such as bleach, alcohol, hydrogen peroxide, and UV light, in addition to creating their own PPE out of materials such as garbage bags, sheets, and cloth. Furthermore, HCP expressed frustration with PPE policies at their workplaces, which continued throughout the early pandemic due to the rapidly changing guidelines and the inability to express their opinions to their institutions. The combination of these concerns left HCP scared of being infected with COVID-19 while at work and subsequently infecting their loved ones at home. Conclusion: It is critical that healthcare institutions understand HCP’s experiences with and feelings towards PPE, as providing the proper protection is vital in ensuring an adequate HCP workforce.

To enhance inclusivity and rigor, many funding agencies and journals now mandate the inclusion of females as well as males in biomedical studies. These mandates have enhanced generalizability and created unprecedented opportunities to discover sex differences. Education in sound methods to consider sex as a subgroup category has lagged behind, however, resulting in a problematic literature in which study designs, analyses, and interpretations of results are often flawed. Here, we outline best practices for complying with sex-inclusive mandates, both for studies in which sex differences are a primary focus and for those in which they are not. Our recommendations are organized within the “4 Cs of Studying Sex to Strengthen Science: Consideration, Collection, Characterization and Communication,” a framework developed by the Office of Research on Women’s Health at the National Institutes of Health in the United States. Following these guidelines should help researchers include females and males in their studies while at the same time upholding high standards of rigor.