Abstract
Sleep disorders are recognized as one of the significant risk factors for premenstrual syndrome (PMS). Therefore, this study aimed to identify the relationship between sleep quality and PMS symptoms among young women. In this cross-sectional study, 252 women from health centers of Qazvin province participated according to the inclusion criteria. The data of premenstrual symptoms and sleep quality was received through online premenstrual symptoms screening (PSST) and the Pittsburgh Sleep Quality Index (PSQI) questionnaires. For analyzing data, ANOVA and chi-square tests were used to evaluate quantitative and qualitative variables. Sampling adequacy was assessed using the Kaiser-Meyer-Olkin (KMO) test. According to the PSST, 28.7% of individuals experienced mild severity, 21.9% experienced moderate severity, and 49.4% experienced severe severity. The correlation between PSQI and PSST showed a significant relationship (p < 0.05) with anger/temper, anxiety/tension, crying/sensitivity to negative responses, depressed mood/disappointment, and fatigue/lack of energy. Based on the results, it has been established that there is a notable correlation between the quality of sleep and the severity of PMS symptoms. This underscores the crucial role of sleep in the management of PMS.
Keywords: Premenstrual syndrome, Sleep quality, PMS, Young women
Subject terms: Gastroenterology, Medical research
Introduction
Premenstrual syndrome (PMS) is a common disorder affecting women of reproductive age. There are several identified symptoms associated with PMS1. PMS is a collection of physical, emotional, and behavioral symptoms that some women experience periodically during the late luteal phase, which is 7–14 days before their menstruation starts2. These symptoms include changes in appetite, irritability, depression, anxiety, lack of concentration, headaches, and sleep problems. The severity of symptoms increases during the week before the start of menstruation but improves or disappears once the period begins3. The prevalence of PMS is estimated to be 48% worldwide, while in Iran it was reported to be 70.8%4. Hypotheses have been proposed to explain the cause of PMS. These include hormonal imbalances such as increased estrogen levels, reduced progesterone levels, changes in the estrogen-progesterone ratio, deficiencies in micronutrients, lack of physical activity, and inappropriate anthropometric indices5.
Primary insomnia is a sleep disorder characterized by chronic difficulty initiating or maintaining sleep, causing significant distress or impairment in daily functioning. The Pittsburgh Sleep Quality Index (PSQI) is reliable and valid for assessing primary insomnia6. Recent reports suggest that poor sleep quality, insomnia, and short sleep duration are related to PMS7.
Considering that studies examining the relationship between sleep quality and PMS are limited, there is still insufficient and inconclusive scientific evidence regarding the direction of this relationship and its precise temporal sequence. Some studies, such as those previously mentioned, have reported the direction of the relationship as being from sleep quality to PMS, while others have suggested the reverse, indicating that PMS influences sleep quality. Also, evidences suggest that female sex hormones can significantly influence mood, particularly in women dealing with PMS. Altogether, relative changes in estrogen or progesterone levels often can appear to coincide with an increase in depressive symptoms and sleep problems8.
Sleep patterns are considered a key modifiable lifestyle risk factor for PMS. The relationship between menstrual problems and poor sleep is not clear. It is uncertain whether menstrual problems cause poor sleep or if poor sleep leads to menstrual problems9. In Baker et al.‘s study, women with PMS reported poorer sleep quality during the late-luteal phase than the follicular phase. This was linked to higher anxiety and more perceived nighttime awakenings10.
Also, the study by Erbil aimed to determine the relationship between PMS and sleep quality among nursing and medical students. The results indicated a significant association between PMS and poor sleep quality11.
Given that there is no definitive cure for PMS, and considering that individuals with this condition may also experience sleep disturbances, which in turn can negatively impact their quality of life, it is essential to conduct studies in this area aimed at identifying the relationship between PMS and sleep disorders. Such research could help, if a relationship is observed, to provide interventional recommendations for improving sleep quality in affected individuals, as well as propose the implementation of future longitudinal studies. The aim of this study is to determine the relationship between PMS and sleep disturbances in these patients.
Material and method
Participants
This study conducted a cross-sectional survey from 2022 to 2023 using an online questionnaire completed by females of reproductive age who were referred to the three health centers in Qazvin, Iran. A total of 252 women participated and completed the online questionnaire based on the inclusion criteria, which required them to have a menstrual cycle. The participants were selected by healthcare professionals at the healthcare centers. The inclusion criteria require participants to be willing to cooperate, have PMS symptoms, and be of reproductive age, but cannot be menopausal, pregnant, or breastfeeding. The exclusion criteria include diagnosed diseases such as diabetes, liver and kidney dysfunction, CVD, cancer, polycystic ovary syndrome, or premature menopause. Participants also cannot be using birth control pills, antidepressants, other psychoactive drugs, thyroid medications, or other hormonal medications. This study was registered with the ethics code IR.QUMS.REC.1401.110 at Qazvin University of Medical Sciences. The participants in the study agreed to take part by completing the questionnaire. It’s important to mention that the participants’ information was kept confidential and used only for the article.
Study design
Methodological quality was evaluated using the checklist from the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement12. In this study, individuals were initially screened based on the entry criteria. Then, the eligible women were informed about the work objectives. Once satisfied, they received the questionnaire link via Google Form. It should be noted that the questionnaires were created online and distributed to eligible women covered by Qazvin city health centers through virtual platforms. In this study, data was collected through demographic questionnaires, premenstrual symptoms screening (PSST), and the Pittsburgh Sleep Quality Index (PSQI). Validity and reliability of questionnaires are proved in previous studies13,14.
The PSST questionnaire is a screening tool used to assess the symptoms of PMS and determine the severity of the disease as well as the impact of the symptoms on individuals’ lives. This questionnaire comprises 19 questions, divided into two parts. The first part has 14 questions related to mood, physical, and behavioral symptoms. The second part includes 5 questions that measure the effects of these symptoms on people’s lives. Each question has four criteria: not at all, mild, moderate, and severe, which are graded from 0 to 3.
The Pittsburgh Sleep Quality Index (PSQI) was used to assess sleep variables. The PSQI measures sleep quality and disturbances over one month and comprises seven components: subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbances, use of sleeping medication, and daytime dysfunction. Each component is scored from 0 to 3, and the sum of scores for these seven components determines the global score, which ranges from 0 to 21. A score higher than 5 indicates poor sleep quality. In a validation study, the developers suggested that a global PSQI score > 5 can diagnose sleep problems with a sensitivity of 89.6% and a specificity of 86.5%, distinguishing patients with sleep issues from healthy controls15.
According to the previous study of Mona S. Hashim et al.16 and considering the prevalence of moderate to severe PMS equal to 63% and considering the type 1 error α = 0.05 and accuracy equal to 4% with the help of the following formula for the number of 560 samples required.
 |
After sending 560 questionnaires to women at the health center, 252 individuals met the entry criteria and were diagnosed with PMS based on the PSST questionnaire.
Data analysis
In this study, ANOVA and chi-square tests were used to evaluate quantitative and qualitative variables, respectively. Sampling adequacy was assessed using the Kaiser-Meyer-Olkin (KMO) test. Eigenvalues higher than 1 were considered to identify effective factors. In order to investigate the relationship between sleep quality and premenstrual syndrome, multivariable linear regression was used. Initially, a univariable logistic regression analysis was performed. Variables with a p-value < 0.25 were considered candidates for inclusion in the multivariable model17. In this research, p < 0.05 was considered statistically, and statistical analyses were conducted using SPSS version 20.
Results
In this study 237 participants with PMS contributed and full fill the questionnaires. The demographic characteristics of the participants are presented in Table 1. The mean age of the participants was 32.41 ± 10.18. Among the participants, 40.1% were married, and 59.9% were single. In a case of educational status, 3.6% of the women had a high school education, while 95.7% had an academic education. In terms of occupation, 33.3% were employed, 50% were students, and 16.3% were housewives. The mean ± SD of the participants’ weight was 62.56 ± 11.49, and the mean ± SD of family members was 3.88 ± 11.2.
Table 1.
Baseline characteristics of the participants.
| Characteristics | Number (%) | |
|---|---|---|
| Marriage status | Married | 101 (40.1) |
| Single | 151 (59.9) | |
| Education | High school | 9 (3.6) |
| Diploma and postgraduate diploma | 45 (17.9) | |
| Bachelor’s degree | 101 (40.1) | |
| Master’s degree | 69 (27.4) | |
| PhD and above | 26 (10.3) | |
| Occupational status | Employee | 85 (33.3) |
| Student | 126 (50.0) | |
| Housewife | 41 (16.3) | |
Table 2 illustrates the classification of PMS severity in patients based on PSST questionnaire. Based on PSST, 28.7% experienced mild, 21.9% experienced moderate, and 49.4% experienced severe severity.
Table 2.
Frequency of PMS symptoms.
| Items | Never frequency (valid percentage) |
Mild frequency (valid percentage) |
Moderate frequency (valid percentage) |
Severe frequency (valid percentage) |
|---|---|---|---|---|
| Anger/irritability | 27 (10.8) | 65 (25.9) | 104 (41.4) | 55 (21.9) |
| Anxiety/tension | 36 (14.3) | 67(26.7) | 109 (43.4) | 39 (15.5) |
| Tearful/sensitive to rejection | 55 (21.9) | 70(27.9) | 84 (33.5) | 42 (16.7) |
| Depressed mood/hopelessness | 47 (18.7) | 77 (30.6) | 75 (29.8) | 53 (21) |
| Decreased interest in work activities | 68 (27) | 85 (33.7) | 70 (27.8) | 29 (11.5) |
| Decreased interest in home activities | 55 (21.8) | 85 (33.7) | 71 (28.2) | 41 (16.3) |
| Decreased interest in social activities | 73 (29) | 78 (31) | 74 (29.4) | 27 (10.7) |
|
Difficulty concentrating (such as not concentrating on a lesson or any other task) |
67 (26.6) | 86 (34.1) | 70 (27.8) | 29 (11.5) |
| Fatigue/lack of energy | 16 (6.4) | 83 (33.1) | 93 (37.1) | 59 (23.5) |
| Overeating/ food cravings | 66 (26.2) | 77 (30.6) | 79 (31.3) | 30 (11.9) |
| Insomnia | 115 (45.8) | 79 (31.5) | 43 (17.1) | 14 (5.6) |
| Hypersomnia (need more sleep) | 66 (26.2) | 70 (27.8) | 88 (34.9) | 28 (11.1) |
| Feeling overwhelmed or out of control | 59 (23.5) | 84 (33.5) | 75 (29.9) | 33 (13.1) |
|
Physical symptoms such as breast pain, headache, muscle/joint pain, abdominal bloating, weight gain |
27 (10.8) | 67 (26.7) | 97 (38.6) | 60 (23.9) |
| Work efficiency/productivity | 72 (28.8) | 85 (34) | 81 (32.4) | 12 (4.8) |
| Relationship with co-workers | 65 (25.8) | 89 (35.3) | 77 (30.6) | 21 (8.3) |
| Relationship with family | 55 (22) | 88 (35.2) | 84 (33.6) | 23 (9.2) |
| Social life activities | 73 (29) | 92 (36.5) | 72 (28.6) | 15 (6) |
| Home responsibilities | 63 (25.1) | 90 (35.9) | 76 (30.3) | 22 (8.8) |
In classifying the severity of the disease in patients based on PMS symptoms, the findings revealed that 28.7% (68 individuals) of the patients were in the mild stage, 21.9% (52 individuals) in the moderate stage, and 49.4% (117 individuals) in the severe stage of the disease.
Table 2 presents the detailed frequency of PMS symptoms along with their percentage (valid percentage). Most of the symptoms fell within the severe range. Also, the maximum intensity of each symptom is bolded in the table.
The analysis of the PMS symptoms subscales in relation to the severity of symptoms among participants with sleep quality is outlined in Table 3. According to the findings, it was found that anger/temper, anxiety/tension, crying/increasing sensitivity to negative responses, depressed mood/disappointment, and fatigue/lack of energy exhibited a significant association with sleep quality (p < 0.05). However, decreased interest in work activities, insomnia, and physical symptoms did not show a significant association (p > 0.05). The results indicate that 78.6% of the participants had good sleep quality, while 21.4% had poor sleep quality. In this investigation, the sleep score was associated with the PMS tool score (β = 0.91; p < 0.05).
Table 3.
The comparison of PMS symptoms based on sleep quality.
| PMSS and subscales | Good sleep frequency (%) |
Sleep disorder frequency (%) |
p-value | |
|---|---|---|---|---|
| Anger/temper | Never | 27 (13.7) | 0 | 0.001 |
| Mild | 60 (30.5) | 5 (9.3) | ||
| Moderate | 73 (37.1) | 31 (57.4) | ||
| Severe | 37 (18.8) | 18 (33.3) | ||
| Anxiety/tension | Never | 36 (18.3) | 0 | 0.002 |
| Mild | 53 (26.9) | 14 (25.9) | ||
| Moderate | 83 (42.1) | 26 (48.1) | ||
| Severe | 25 (12.7) | 14 (25.9) | ||
|
Crying/increasing sensitivity to negative response |
Never | 51 (25.8) | 4 (7.5) | 0.003 |
| Mild | 59 (29.8) | 11 (20.8) | ||
| Moderate | 60 (30.3) | 24 (45.3) | ||
| Severe | 28 (14.1) | 14 (26.4) | ||
|
Depressed mood/ disappointment |
Never | 44 (22.2) | 3 (5.6) | 0.001 |
| Mild | 65 (32.8) | 12 (22.2) | ||
| Moderate | 58 (29.3) | 17 (31.5) | ||
| Severe | 31 (15.7) | 22 (40.7) | ||
|
Decreased interest in work activities |
Never | 57 (28.8) | 11 (20.4) | 0.2 |
| Mild | 69 (34.8) | 16 (29.6) | ||
| Moderate | 52 (26.3) | 18 (33.3) | ||
| Severe | 20 (10.1) | 9 (16.7) | ||
|
Fatigue/lack of energy |
Never | 13 ( (6.6) | 3 (5.7) | 0.03 |
| Mild | 73 (36.9) | 10 (18.9) | ||
| Moderate | 72 (36.4) | 21 (39.6) | ||
| Severe | 40 (20.2) | 19 (35.9) | ||
| Insomnia | Never | 94 (47.7) | 21 (38.9) | 0.4 |
| Mild | 62 (31.5) | 17 (31.5) | ||
| Moderate | 32 (16.2) | 11 (20.4) | ||
| Severe | 9 (4.6) | 5 (9.3) | ||
|
Physical symptoms (breast pain, headache, muscle/joint pain, abdominal bloating, weight gain) |
Never | 23 (11.7) | 4 (7.4) | 0.06 |
| Mild | 59 (29.9) | 8 (14.8) | ||
| Moderate | 70 (35.5) | 27 (50) | ||
| Severe | 45 (22.8) | 15 (27.8) | ||
PSQI, Pittsburgh sleep quality index.
A logistic regression analysis was employed to examine the association between menstrual issues and sleep quality. The findings of this analysis are presented in Table 4.
Table 4.
The results of logistic regression the association between menstrual issues and sleep quality.
| Variable | B | S.E. | Sig. | Exp(B) | 95% C.I. for EXP(B) | |
|---|---|---|---|---|---|---|
| Lower | Upper | |||||
| PMS symptoms | 0.043 | |||||
| PMS symptoms (Mild) | – 1.132 | 0.452 | 0.012 | 0.322 | 0.133 | 0.781 |
| PMS symptoms (Moderate) | − 0.194 | 0.392 | 0.621 | 0.824 | 0.382 | 1.778 |
| Age | − 0.015 | 0.019 | 0.418 | 0.985 | 0.950 | 1.022 |
| BMI | − 0.023 | 0.042 | 0.584 | 0.977 | 0.900 | 1.061 |
As the results of the logistic regression test showed, PMS symptoms are related to sleep quality by controlling the effect of age variables and BMI (p-value < 0.05).
Discussion
Several studies have identified sleep habits as one of the primary modifiable lifestyle risk factors for PMS. Nevertheless, it remains unclear whether menstrual problems lead to poor sleep or vice versa9. Considering that sleep disturbances and menstrual issues may influence one another and create a vicious circle18. Limited research in this field prompted this study to investigate the correlation between sleep quality and the severity of premenstrual syndrome symptoms in women of reproductive age.
Findings revealed that the majority of the participants (49.4%) had severe PMS symptoms, while mild and moderate PMS symptoms were observed in 28.7% and 21.9% of the participants, respectively. Also, the results indicate that 78.6% of the participants had good sleep quality, while 21.4% had poor sleep quality, indicating that sleep disturbances can significantly worsen the condition. A cross-sectional study conducted by Jeong et al.9 investigated the effect of sleep patterns on PMS and primary dysmenorrhea in 519 Korean teenage girls aged 15–18 years during COVID-19 quarantine. The results indicated that sleeping less than 5 h was associated with worsening premenstrual symptoms. Also, components such as sleep latency, sleep disturbance, use of sleeping medication, and disruption in daily functioning were related to the aggravation of these symptoms. This study pointed to the importance of sleep quality, as it was reported that girls who had poor sleep quality experienced more severe PMS symptoms and worse functional disorders compared to those who had good sleep quality9. Furthermore, another online study performed in 2023 on 143 female students in Korea discovered that women with PMS had poorer sleep quality compared to those without PMS. Specifically, these women required more time to fall asleep and had shorter sleep duration19. An epidemiological study conducted in Sao Paulo on 230 women showed that those with PMS had poorer sleep quality and experienced more insomnia compared to the control group. However, contrary to the results of a previous study, women with PMS had longer sleep duration. On the other hand, factors such as sleep latency, daytime sleepiness, and sleep efficiency were not associated with PMS20.
The menstrual cycle is regulated by hormones like estrogen, progesterone, prolactin, and growth hormone. These hormones not only affect reproduction but also impact the circadian rhythm and sleep. Consequently, hormonal imbalances can lead to disruptions in sleep patterns21. Pain and stress caused by menstruation can also lead to insomnia, which can disrupt the menstrual cycle by altering estrogen and progesterone levels22. In addition, during the luteal phase, hormonal imbalances of the ovary, such as a decrease in estrogen and an increase in progesterone, are associated with changes in the level of gamma-aminobutyric acid (GABA) and brain-derived neurotrophic factor (BDNF) in the brain23. Since GABA and BDNF are neural factors affecting sleep and mood regulation in the central nervous system, Changes in their levels can ultimately lead to sleep disorders, cognitive problems, and mood swings during PMS24. In this regard, reports indicate that in Premenstrual dysphoric disorder (PMDD) patients with mood disorders, GABA levels in the cerebral cortex were significantly reduced compared to healthy individuals25. Among other possible mechanisms, we can mention a decrease in melatonin levels during the follicular and luteal phases of PMS. Although the exact process of melatonin secretion and its disruption of the circadian clock in PMS-related issues has not been determined yet, studies suggest that women with PMDD experience sleep disorders due to a decrease in melatonin levels26. The results of a clinical trial by Shabani also revealed that after 12 weeks of melatonin supplementation, the sleep quality of patients with polycystic ovary syndrome (PCOS) increased remarkably27.
Due to the diversity of PMS symptoms, limited studies have explored the relationship between sleep and PMS components. This study specifically investigated this association. In this research, a substantial connection was noted between symptoms such as anger, anxiety and tension, sensitivity to negative response, depressed mood and disappointment, as well as fatigue and lack of energy with sleep quality (p < 0.05). However, physical symptoms (breast pain, headache, muscle/joint pain, abdominal bloating, and weight gain), insomnia, and decreased interest in work-related activities did not have a notable impact on the quality of sleep (p > 0.05).
A survey by Erbil in 2020 aimed to determine the relationship between PMS and sleep quality among 313 medical and nursing students. In accordance with our results, this study also demonstrated that depression was a significant predictor of sleep quality among the components of PMS. However, the study found no evidence of a correlation between anxiety, fatigue, pain, and sleep quality, which contradicted our reports28. Nonetheless, unlike the present study, the findings of another study carried out on nurses in Thailand (2017) indicated that sleep quality was only significantly associated with physical symptoms (breast tenderness, headache, joint and muscle pain, weight gain, and bloating)29. The outcomes of an investigation on 4122 young women aged 12–25 years in upper Egypt reported that women who slept less than 7–8 h per day had more premenstrual spasms compared to those who slept 8 h or more. It is noteworthy that insomnia had a significant relationship with premenstrual symptoms such as fatigue, headache, and breast pain. However, no significant relationship between sleeping hours and most menstrual symptoms was observed in this study13. Nevertheless, according to the Jang study in 2022, there was no significant correlation between sleep duration and the severity of PMS symptoms among 304 female nursing students30. The contradictions in the results of studies can be partially attributed to differences in data collection methods, participant numbers, and respondent errors.
Based on scientific reports, PMS results in impaired interpersonal relationships or workplace performance in 3–8% of women of reproductive age31. In the study by Hatice et al., it was found that nurses with PMS reported lower job satisfaction, which was linked to work-related stress and a decline in their job performance. The results also revealed a negative relationship between changes in sleep patterns and work-related stress, as well as nurses’ job performance32. The results of our findings also did not indicate a significant relationship between sleep quality and decreased interest in work activities among individuals with PMS.
There are some limitations in this study. First, we only examined the relationship of a few components of PMS symptoms with sleep quality despite the wide range of PMS symptoms. Second, premenstrual symptoms and sleep quality were self-reported by the participants, and no examination or laboratory tests were conducted to determine them. Furthermore, conducting this study online may lead to less accurate responses from participants. Consequently, this may limit the generalizability of the current findings.
Conclusions
According to the findings of this study, a significant association was observed between sleep quality and PMS and the subscales of anger, anxiety, sensitivity to negative response, depressed mood and disappointment, and fatigue. This suggests the importance of addressing sleep quality in managing PMS symptoms and underscores the potential benefits of interventions targeting improved sleep in alleviating various aspects of premenstrual syndrome. Further research in this field could provide valuable insights and assist in developing more effective treatment strategies for individuals experiencing PMS symptoms.
Acknowledgements
We would like to express our deepest gratitude to all stakeholders, health care providers, and individuals who participated in this study.
Author contributions
Mighani and Javadi designed the study and analyzed the data. Shivyari and Razzaghi collected the data and helped to write the paper. Ranjbaran contributed to the data analysis. Samavat and Amerzadeh participated in the design of the study and editing of the paper. All authors have read and approved the final manuscript.
Data availability
The datasets used and/or analyzed during the current study available from the corresponding author on reasonable request. The entire dataset is in Farsi language. The Data can be available in English language for the readers and make available from the corresponding author on reasonable request.
Competing interests
The authors declare no competing interests.
Ethics approval and consent to participate
The present study was approved by the ethical committee Qazvin University of Medical Sciences (ethics code IR.QUMS.REC.1401.110). The Ethical Committee approved all experimental protocols. All methods were carried out in accordance with relevant guidelines and regulations. We provided the participants or their legal guardian(s) with an information sheet, reassured them about anonymity, freedom to withdraw, confidentiality and explained the study’s purpose, and obtained their informed consent form.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The datasets used and/or analyzed during the current study available from the corresponding author on reasonable request. The entire dataset is in Farsi language. The Data can be available in English language for the readers and make available from the corresponding author on reasonable request.