Premenstrual Disorders, Timing of Menopause, and Severity of Vasomotor Symptoms

Yang, Yihui; Valdimarsdóttir, Unnur A.; Manson, JoAnn E.; Sievert, Lynnette Leidy; Harlow, Bernard Leslie; Eliassen, A. Heather; Bertone-Johnson, Elizabeth R.; Lu, Donghao

doi:10.1001/jamanetworkopen.2023.34545

Cited by 6 publications

References 68 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Correlation of White Matter Microstructure MRI and Inflammatory Cytokine Alterations With Symptom Severity in Premenstrual Syndrome

Duan,

Qin,

Lai

et al. 2024

Magnetic Resonance Imaging

View full text Add to dashboard Cite

BackgroundWomen with premenstrual syndrome (PMS) are at increased risk for depression throughout their lives. White matter (WM) microstructure and inflammatory cytokine alterations have been proposed in its etiology.PurposeTo investigate whether WM, assessed using diffusion tensor imaging (DTI), and inflammatory cytokine levels are altered in PMS, and to examine the relationships between WM microstructure, inflammatory cytokines, and symptom severity.Study TypeProspective.SubjectsForty‐two PMS patients and 58 healthy controls (HCs), categorized according to the daily record of severity of problems (DRSP).Field Strength/Sequence3‐T, echo planar imaging DTI.AssessmentFractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) were measured by using tract‐based spatial statistics (TBSS). Venous blood was collected to measure cytokines, including interleukin‐1β (IL‐1β) and tumor necrosis factor‐α (TNF‐α). Symptoms were assessed by using the DRSP.Statistical TestsTwo‐sample t test or Mann–Whitney U test were used to compare the DRSP and cytokines. Abnormal DTI metrics in WM were extracted and the differences between groups were analyzed by using two sample t‐tests. Spearman's correlation (r) was used to assess the relationship between DTI metrics, cytokines, and DRSP. A P‐value <0.05 with FDR correction was considered statistically significant.ResultsCompared with HCs, PMS patients showed significantly lower FA in the corpus callosum and corona radiata, and significantly higher MD, AD, and RD in the corticospinal tract (CST), and significantly higher MD and RD in the anterior thalamic radiation (ATR). These differential metrics were significantly correlated with DRSP. Patients showed significantly higher IL‐1β and TNF‐α than HCs. Moreover, TNF‐α correlated positively with MD, AD, and RD in both groups (r range, 0.256–0.315).Data ConclusionAlterations of WM microstructure and IL‐1β and TNF‐α may be associated with PMS symptom severity, and TNF‐α may correlate with DTI metrics of CST and ATR pathways.Evidence Level1Technical EfficacyStage 2

show abstract

Correlation of White Matter Microstructure MRI and Inflammatory Cytokine Alterations With Symptom Severity in Premenstrual Syndrome

Duan,

Qin,

Lai

et al. 2024

Magnetic Resonance Imaging

View full text Add to dashboard Cite

show abstract

Wearable-Measured Heart Rate Variability and Premenstrual Disorder Symptoms across Menstrual Cycle

Pan,

Zhou,

Chen

et al. 2024

Preprint

View full text Add to dashboard Cite

IMPORTANCE Premenstrual disorders (PMDs), characterized by affective symptoms before menses, significantly impact women who are suffering. Current diagnostic tools are time-consuming and challenging in practice, resulting in delay in detection and treatment. There is an urgent need to identify objective and easily accessible measures to streamline the diagnostic process for PMDs. Objectives To investigate the menstrual fluctuation of wearable device-based real-time heart rate variability (HRV) through menstrual cycles and its associations with premenstrual disorders (PMD) symptoms. Design, Setting, and Participants We conducted a prospective study of female participants nested from the Care of Premenstrual Emotion Cohort. Exposure outcome and measures Daily HRV metrics (SDNN, rMSSD, LF, HF, and LF/HF) were estimated from consecutive RR-intervals (RRI) collected by the Huawei Fitness Tracker 6 Pro at 5-minute intervals over 1-2 menstrual cycles and averaged on records during 03:00-05:00 a.m. PMD symptoms were assessed with the Daily Record of Severity of Problems on a daily basis. HRV variability across cycles was described using descriptive statistics and splines, while associations between HRV metrics and PMD symptoms were estimated using a mixed-effect model. Results In total, 193 participants (with 68 prospectively confirmed PMDs) were included, with measures from 293 menstrual cycles. In both women with and without PMDs, SDNN, rMSSD, and HF decreased before menses and increased afterwards; the increase trends were more pronounced in women without PMDs. During the week before or after menses, levels of these HRV metrics were inversely associated with PMD symptoms among women with PMDs (e.g., rMSSD, postmenstrual week, β = -0.036 per SD, 95% CI: -0.048 to -0.065), whereas null association was noted for those without PMDs (β = -0.001, 95% CI -0.011 to 0.009; P-for-difference < 0.001). The association was particularly stronger with affective symptoms than with physiological symptoms, and more pronounced during the premenstrual week among women with premenstrual dysphoric disorder compared with those with premenstrual syndrome. Conclusion and Relevance Our findings suggest that wearable device-estimated HRV metrics fluctuate across menstrual cycles, with varying strengths of association with PMD symptoms between individuals with and without PMDs, which may aid future diagnostic process for PMDs.

show abstract

Premenstrual disorders and risk of sick leave and unemployment: a prospective cohort study of 15,857 women in Sweden

Yu,

Yang,

Hysaj

et al. 2024

Preprint

View full text Add to dashboard Cite

Importance: Premenstrual disorders (PMDs) are prevalent and significantly impair women's quality of life. Yet, the long-term impact on work capacity is not well understood. Objective: To prospectively examine the association between PMDs and work incapacity, including sick leave and unemployment. Setting, Design and Participants: A prospective cohort study of 15,857 women aged 15-60 years and employed at baseline in the LifeGene Study with linkage to population and health registers in Sweden. Exposure: PMDs were identified via register-based clinical diagnoses and symptom questionnaires. Main Outcomes and Measures: We extracted information on sick leave and unemployment status from national registers. We used Poisson regression to estimate incidence rate ratios (IRRs) of sick leave and unemployment comparing women with PMDs to those without. Results: In total, 2,585 (16.30%) women (mean age 32.52 years) reported symptom burden indicative of probable a PMD. With a median follow-up of 9.17 years, 6,741 (42.51%) and 1,485 (9.36%) women were exposed to at least one sick leave and unemployment during follow-up, respectively. Compared to women without PMDs, those with PMDs had 40% and 27% higher risks of sick leave (fully adjusted-IRR 1.40, 95% CI 1.31-1.49) and unemployment (IRR 1.27, 95% CI 1.10-1.46), respectively. The association was particularly stronger for long-term sick leave (≥ 90 days) (IRR 1.69, 95% CI 1.50-1.91), and sick leave due to depression (IRR 1.41, 95% CI 1.27-1.56). In addition, comparable associations for sick leave and unemployment were yielded, when comparing women with and without a history of depression/anxiety. Conclusions: Employed women with PMDs are at increased risk of sick leave and unemployment, underscoring the potential long-term health and socioeconomic consequences of this prevalent condition. Improved clinical management of comorbidities and workplace policies are needed to support women affected by PMDs.

show abstract

Premenstrual Disorders, Timing of Menopause, and Severity of Vasomotor Symptoms

Cited by 6 publications

References 68 publications

Correlation of White Matter Microstructure MRI and Inflammatory Cytokine Alterations With Symptom Severity in Premenstrual Syndrome

Correlation of White Matter Microstructure MRI and Inflammatory Cytokine Alterations With Symptom Severity in Premenstrual Syndrome

Wearable-Measured Heart Rate Variability and Premenstrual Disorder Symptoms across Menstrual Cycle

Premenstrual disorders and risk of sick leave and unemployment: a prospective cohort study of 15,857 women in Sweden

Contact Info

Product

Resources

About