Are premenstrual syndrome and dysmenorrhea related to the personality structure of women? A descriptive relation-seeker type study

Network structure of complex interactions of premenstrual syndrome and influencing factors in young adult women

BACKGROUND

In the transition phase from adolescence to adulthood, premenstrual syndrome (PMS) occurs more commonly, with a variety of symptoms. The occurrence of PMS may be the result of a combination of demographic, physiological, psychological and sociological factors. This study aimed to identify the central symptoms of PMS, and explored the complex influencing factors especially the one-to-one inter-relationships factors with specific symptoms.

METHOD

This is a cross-sectional study conducted in mainland China. 3458 young adult women were assessed. Using the Premenstrual Syndrome Scale (PSS) to assess the PMS, and PSS score was over 6 divided into PMS group, and vice versa. Influencing factors were assessed by a set of self-reported questionnaire. Network analysis was used to examined the interplay of PMS, whilst also considering the influencing factors of PMS.

RESULTS

In summary, 1479 participants were in PMS group. Anxiety had the highest strength centrality (1.12/1.09), shown higher centrality in the both network. Swelling of the hands or feet also shown higher strength centrality (0.89) in PMS group. PMS is associated with a higher history of dysmenorrhea, and neurotic personality. Neurotic personality - depressed mood/nervousness (0.27/0.23), history of dysmenorrhea - abdominal distension (0.21), had significantly higher weight than other edges in PMS group.

CONCLUSION

Anxiety was the most central symptom in the network, and was closely associated with other symptoms like depressed mood, which provided additional evidence for the centrality of emotional features in PMS. Moreover, the influencing factors of PMS combined demographic, physiological, psychological, and sociological factors. According to the central symptoms and factors affecting the specific PMS symptoms in young adult women, targeted intervention is helpful to prevent and alleviate PMS.

LIMITATION

Cross-sectional design cannot infer the directionality of the associations between variables. All data is self-reported with recall bias and the edge weights across the constructs of influencing factors and PMS were fairly small.

Development and validation of risk prediction model for premenstrual syndrome in nurses: results from the nurses-based the TARGET cohort study

Objective

Premenstrual syndrome (PMS) stands as a significant concern within the realm gynecological disorders, profoundly impacting women of childbearing age in China. However, the elusive nature of its risk factors necessitates investigation. This study, therefore, is dedicated to unraveling the intricacies of PMS by focusing on nurses, a cohort with unique occupational stressors, to develop and validate a predictive model for assessing the risk of PMS.

Methods

This investigation employed a multi-center cross-sectional analysis drawing upon data from the TARGET Nurses' health cohort. Utilizing online survey versions of the Premenstrual Syndrome Scale (PMSS), a comprehensive dataset encompassing physiological, social, psychological, occupational, and behavioral variables was collected from 18,645 participants. A stepwise multivariate logistic regression analysis was conducted to identify independent risk factors for PMS. Furthermore, a refined variable selection process was executed, combining the Least Absolute Shrinkage and Selection Operator (LASSO) method with 10-fold cross-validation. The visualization of the risk prediction model was achieved through a nomogram, and its performance was evaluated using the C index, receiver operating characteristic (ROC) curves, and the calibration curves.

Results

Among the diverse variables explored, this study identified several noteworthy predictors of PMS in nurses, including tea or coffee consumption, sleep quality, menstrual cycle regularity, intermenstrual bleeding episodes, dysmenorrhea severity, experiences of workplace bullying, trait coping style, anxiety, depression and perceived stress levels. The prediction model exhibited robust discriminatory power, with an area under the curve of 0.765 for the training set and 0.769 for the test set. Furthermore, the calibration curve underscored the model's high degree of alignment with observed outcomes.

Conclusion

The developed model showcases exceptional accuracy in identifying nurses at risk of PMS. This early alert system holds potential to significantly enhance nurses' well-being and underscore the importance of professional support.

Is there a relationship between internalized misogyny and premenstrual syndrome and dysmenorrhea in young women? A descriptive-relational study

AIM

This study utilized a descriptive and relational design to determine the relationship between young women's experiences of premenstrual syndrome (PMS) and dysmenorrhea with internalized misogyny.

METHODS

A total of 487 individuals were accessed. Data were collected through the "Personal Information Form" prepared by the researchers, the "Functional and Emotional Measure of Dysmenorrhea" the "Premenstrual Syndrome Scale," and the "Internalized Misogyny Scale."

RESULTS

The internalized misogyny scale mean score had significant effects on the functional and emotional measure of dysmenorrhea mean score (p < 0.05). The internalized misogyny scale mean score was found to have a statistically significant effect on the premenstrual syndrome scale (p < 0.05).

CONCLUSIONS

This study found that young women's internalized misogyny was highly correlated with PMS and dysmenorrhea, and increased internalized misogyny also increased the severity of PMS and dysmenorrhea in young women.

Association between Neuroticism and Premenstrual Affective/Psychological Symptomatology

Neuroticism and premenstrual conditions share pleiotropic loci and are strongly associated. It is presently not known which DSM-5 symptoms of premenstrual syndrome/premenstrual mood disorder are associated with neuroticism. We enrolled 45 study participants to provide prospective daily ratings of affective ("depression", "anxiety, "anger", "mood swings") and psychological ("low interest", "feeling overwhelmed", and "difficulty concentrating") symptoms across two-three menstrual cycles (128 total cycles). Generalized additive modeling (gam function in R) was implemented to model the relationships between neuroticism and the premenstrual increase in symptomatology. Significance level was adjusted using the False Discovery Rate method and models were adjusted for current age and age of menarche. Results of the association analysis revealed that "low interest" (p ≤ 0.05) and "difficulty concentrating" (p ≤ 0.001) were significantly associated with neuroticism. None of the remaining symptoms reached statistical significance. The late luteal phase of the menstrual cycle is characterized by complex symptomatology, reflecting a physiological milieu of numerous biological processes. By identifying co-expression between neuroticism and specific premenstrual symptomatology, the present study improves our understanding of the premenstrual conditions and provides a platform for individualized treatment developments.