Effect of sleep quality on the severity of perimenstrual symptoms in Japanese female students: a cross-sectional, online survey =============================================================================================================================== * Sakura Oda * Noriaki Maeda * Tsubasa Tashiro * Rami Mizuta * Makoto Komiya * Satoshi Arima * Takaaki Nagasawa * Koichi Naito * Yukio Urabe ## Abstract **Objectives** To investigate the relationship between sleep quality and perimenstrual symptoms among Japanese female students. **Design** Observational, cross-sectional, online survey **Setting** We used an online questionnaire to collate responses from Japanese female students on sleep quality and perimenstrual symptoms. **Participants** A total of 298 female students aged 18–25 years in Japan were included in this study. **Primary and secondary outcome measures** The Menstrual Distress Questionnaire (MDQ) was used to assess the severity of perimenstrual symptoms for three periods—premenstrual, menstrual and postmenstrual—and the Japanese version of the Pittsburgh Sleep Quality Index was used to assess sleep quality. The MDQ scores were compared between two groups (normal-sleep quality and low-sleep quality) using Mann-Whitney U test. In addition, multiple logistic regression analysis was performed, and the MDQ subscales that showed significant differences between the groups were used as independent variables. The MDQ subscale that was strongly associated with sleep quality was calculated. **Results** Of the female students, 160 were classified into the normal-sleep quality group and 138 into the low-sleep quality group. The total MDQ scores were significantly higher in the low-sleep quality group at all phases of the menstrual cycle (respectively p<0.05). Among the MDQ subscales, ‘pain’ during menstruation and ‘concentration’ in the premenstrual and postmenstrual stages were associated with sleep quality (respectively p<0.05). **Conclusions** Improving sleep quality was one possible strategy to reduce the severity of perimenstrual symptoms. These results may provide useful information for Japanese female students who suffer from perimenstrual symptoms. * Surveys and Questionnaires * SLEEP MEDICINE * Primary Healthcare ### STRENGTHS AND LIMITATIONS OF THIS STUDY * This study conducts an online survey among female students aged 18–25 years in Japan. * This study adhered to the recommendations of the Checklist for Reporting Results of Internet E-Surveys. * As this study involved a retrospective online survey about past sleep quality and perimenstrual symptoms, recall bias may have influenced the findings in this study. * Since it was a cross-sectional study, the causal relationship between sleep quality and perimenstrual symptoms could not be clearly established. ## Introduction Perimenstrual symptoms are varied and comprise physical, emotional and behavioural symptoms. They occur during premenstrual, menstrual and postmenstrual periods. Approximately 16–91% of women experience perimenstrual symptoms, such as irritability, depression, weight gain and back pain.1 These are important health issues that can lead to a decline in the quality of life of young women, including students.2 Additionally, missing classes due to dysmenorrhoea and other perimenstrual symptoms causes a decline in the academic performance of female students.3 Unhealthy lifestyle habits can affect perimenstrual symptoms.4 Throughout the menstrual cycle, changes in the secretion of female hormones, including oestrogen and progesterone, occur.5 These changes have various effects on a woman’s body and mind, causing perimenstrual symptoms. An example of lifestyle influences on these symptoms is the consumption of trans-fatty acids, which are abundant in fast food and increase the levels of prostaglandins, consequently causing dysmenorrhoea and highlighting that an unbalanced diet can lead to increased pain.4 Exercise could also be associated with perimenstrual symptoms. Reportedly, the secretion of estradiol during exercise increases serotonin secretion, which reduces the negative effects of perimenstrual symptoms.6 These reports suggest that lifestyle habits are related to perimenstrual symptoms in terms of hormone secretion. Sleep, one of the lifestyle habits, is an important aspect of human life, with approximately one-third of life’s existence spent sleeping.7 The hypothalamus plays an important role in sleep and is a regulator of sleep and wakefulness.8 It contains gonadotropin-releasing hormone (GnRH) neurons, which drive the menstrual cycle by secreting GnRH, which helps regulate female hormone levels.9 Additionally, a direct synaptic connection exists between the sleep centre of the brain and GnRH neurons, and deep sleep activates GnRH pulse generators.10 Thus, it is possible that sleep and perimenstrual symptoms, which are both regulated by the hypothalamus, may be closely related. Sleep is characterised by sleep duration and quality, and distinguishing between these two characteristics is essential.11 Compared with sleep quality, sleep duration assesses sleep objectively and refers to the duration of sleep.12 In contrast, sleep quality is evaluated subjectively and is defined as a sense of rest on waking and satisfaction with sleep.12 Although some overlap exists between these two characteristics, they are considered distinct and independent.13 Reportedly, short sleep duration (<6 hours/day) is associated with moderate-to-severe dysmenorrhoea, revealing a relationship between sleep duration and perimenstrual symptoms.14 However, no study has examined the relationship between sleep quality and perimenstrual symptoms. Therefore, this study aimed to examine the involvement of sleep quality in perimenstrual symptoms in Japanese female students and propose strategies to alleviate perimenstrual symptoms. ## Methods ### Patient and public involvement The questionnaire design involved female students. After the questionnaire was drafted, it was pretested with 20 Japanese female students who were not included in the main study. The study was conducted with female students residing throughout Japan and was not restricted to any region, such as prefectures. We plan to widely disseminate the findings of this study to the public by sharing information on social media and so on. ### Study design An observational, cross-sectional, online survey of Japanese female students aged 18–25 years was conducted from 8 November 2022 to 2 February 2023 in Japan. The survey was conducted using Google Forms (Alphabet Inc., Mountain View, CA, USA) (see online supplemental file 1). An online survey was disseminated nationwide to female students aged 18–25 years using the URL of the questionnaire through a snowball sampling method, without identifying the geographical area. Before the survey questions began, a summary of the survey instructions, the purpose of the survey, the time required to complete it and the following instructions to the participants were provided: participants can answer questions anonymously, answer just once and could decline participation at any point during the survey. Responses were used solely for research purposes. Participants could commence the questionnaire after checking a consent box, thereby agreeing to participate in the study. Only those who consented to participate in the survey after reviewing the survey summary and instructions proceeded to answer the questions. Examples of statements were provided for questions that participants found difficult to understand to prevent incorrect inputs. Data files containing responses were secured with a password to enhance protection. The inclusion criteria were (a) agreeing to participate in this study, (b) Japanese female students aged between 18 and 25 years and (c) residing in Japan at the time of the survey. The exclusion criteria were (a) had a current history or history of gynaecological disorders or possible secondary dysmenorrhoea,15 (b) had a current history or history of psychiatric disorders and (c) current history of daily hormonal pill intake. Based on the self-reported responses of the participants, their eligibility for the inclusion and exclusion criteria was determined. This study adhered to the recommendations of the Checklist for Reporting Results of Internet E-Surveys.16 ### Supplementary data [[bmjopen-2024-093197supp001.pdf]](pending:yes) ### Question items The question items were mainly related to sleep quality and the severity of perimenstrual symptoms. They included basic information and sociodemographic and lifestyle characteristics. Basic information included age, age at menarche, height and weight for body mass index (BMI; kg/m2) calculation, duration of dysmenorrhoea, current history and history of gynaecological or psychiatric disorders, and medications for internal use related to these disorders. Sociodemographic characteristics included questions regarding part-time job (yes/no) and living status (alone/with others). Lifestyle characteristics included questions regarding alcohol intake (low/high: no alcohol consumption or up to two drinks per week/more), smoking (yes/no), breakfast (eating/not eating), eating between meals (eating/not eating), caffeine consumption (yes/no: ≥3 times/week), studying until bedtime (yes/no: ≥3 times/week), watching TV until bedtime (yes/no: ≥3 times/week) and screen time (min/day) related to leisure and study.17 18 The Japanese version of the Pittsburgh Sleep Quality Index (PSQI-J) was used to rate sleep quality in the past month. The PSQI-J has been used and validated in a previous study that assessed sleep quality.19 20 Participants answered questions regarding their sleep over the past month, and the overall score (range, 0–21) was calculated as the total score of seven factors presented in questions 1–7: subjective sleep quality, time to fall asleep, sleep duration, sleep efficiency, sleep difficulty, use of sleeping pills and difficulty in staying awake during the day. Subjective sleep quality was assessed using one question rated on a four-point Likert scale (very good, quite good, quite bad and very bad). Time to fall asleep was assessed using two questions regarding the time from bedtime to falling asleep. Sleep duration was rated in four stages (>7 hours; >6 hours but ≤7 hours; ≥5 hours but ≤6 hours and <5 hours). Sleep efficiency was calculated by dividing sleep duration by the total number of hours in bed. Sleep difficulty was assessed using nine questions regarding waking up in the middle of the night, difficulty falling asleep soon after going to bed, feeling cold, having bad dreams, getting up to use the restroom, difficulty in breathing correctly, snoring loudly and coughing, feeling pain or having other reasons for sleep disorders. The use of sleeping pills and difficulty in staying awake during the day were rated on a four-point Likert scale (not once, less than once per week, once or twice per week and three or more times per week). A total PSQI-J score of 5 and below indicates normal-sleep quality, and 6 and above indicates low-sleep quality.19 The Menstrual Distress Questionnaire (MDQ) has long been used as a measure to evaluate the severity of perimenstrual symptoms, and its Japanese version has been validated.21 22 The index assesses responses to 46 questions on eight subscales of perimenstrual symptoms.23 Responses on the most recent symptoms were rated on a six-point scale (1: no reaction at all; 6: acute or partially disabling). High scores indicated increased severity of perimenstrual symptoms. We used six subscales comprising pain, water retention, autonomic reaction, negative affect, concentration and behavioural change; two subscales (mood elevation and control), with higher scores indicating better symptoms, were excluded. Each symptom was assessed for three periods: premenstrual, menstrual and postmenstrual. ### Statistical analysis The respondents were divided into normal-sleep quality and low-sleep quality groups based on the PSQI-J cut-off value of six points.19 Data collected from the survey were processed using IBM SPSS V.28.0 for Windows (IBM Japan Co., Ltd., Tokyo, Japan). Before conducting the analysis, the Shapiro-Wilk test was used to assess the normality of all data. Basic information and lifestyle characteristics, MDQ total scores and subscales in each menstrual period were compared between both groups using the Mann-Whitney U test. The required sample size was calculated using G*Power 3.1. The analysis, with an effect size of *d*=0.5 and an alpha level of α=0.05, indicated a statistical power of 0.801, with each group requiring a sample size of 67. χ2 tests were used to assess sociodemographic and lifestyle characteristics. Effect sizes were calculated to assess not only whether the differences and associations were statistically significant but also the practical significance of these effects. Specifically, the phi coefficient ‘φ’ was used for the χ2 test and the correlation coefficient (r) for the Mann-Whitney U test as indicators of effect size. These effect size measures provided additional context, contributing to the interpretation of the magnitude of the observed effects and their practical relevance beyond mere statistical significance. Multiple logistic regression analysis was conducted separately for each menstrual phase (premenstrual, menstrual and postmenstrual) to identify the relationship between the MDQ subscale scores and sleep quality. For analysis, a PSQI-J score<6 was coded as 0, and a PSQI-J score≥6 was coded as 1. Normal- or low-sleep quality was set as the dependent variable, and MDQ subscales demonstrated statistically significant differences (p-values<0.05) between the normal- and low-sleep quality groups in group comparisons and were selected as independent variables for the analysis (crude model). Additionally, adjustments were made for age (adjusted model) as hormonal balance changes with age.24 The variance inflation factor, a statistic used to measure possible multicollinearity among predictors or independent variables, was computed.25 Multiple variables were employed as independent variables, and to address the potential issue of multiple comparisons, Bonferroni correction was applied. ORs were determined only for the logistic regression analysis to assess the strength and direction of the associations. For all statistical tests, 95% CIs were calculated to evaluate the precision and reliability of the estimates. Regarding sample size calculation, the number of participants per independent variable should be ≥10 based on a previous study.26 In the present study, 4–7 MDQ subscales were used as independent variables. Therefore, it was necessary to include at least 70 participants each in the normal- or low-sleep quality groups. The significance level was set at 0.05. ## Results The survey was distributed among 850 participants, of which 366 (response rate: 43.1%) provided responses. Of the respondents, 68 were excluded (34 respondents had a current history or history of gynaecological disorders or possible secondary dysmenorrhoea, 32 respondents were taking hormone medication, 1 respondent had a current history or history of psychiatric disorders and 1 respondent answered insufficiently). Thus, 298 respondents were included in the final analysis. Of the 298 participants, 160 were classified into the normal-sleep quality group and 138 into the low-sleep quality group based on the PSQI-J cut-off value points (figure 1). ![Figure 1](http://bmjopen.bmj.com/https://bmjopen.bmj.com/content/bmjopen/15/2/e093197/F1.medium.gif) [Figure 1](http://bmjopen.bmj.com/content/15/2/e093197/F1) Figure 1 Flowchart of this study. ### Basic information, sociodemographic characteristics and lifestyle characteristics No significant differences in age, age at menarche, BMI, part-time job and living status were observed between the two groups, as shown in table 1. View this table: [Table 1](http://bmjopen.bmj.com/content/15/2/e093197/T1) Table 1 Basic information, sociodemographic characteristics and lifestyle characteristics As shown in table 1, no significant differences in alcohol intake, smoking, eating between meals, caffeine consumption, studying until bedtime, watching TV until bedtime and screen time were observed between the two groups. In contrast, a significant difference in breakfast consumption was observed between the two groups, with a significantly higher number of students eating breakfast in the normal-sleep quality group compared with that in the low-sleep quality group (p=0.023). ### Comparison of MDQ total scores and subscale scores between the two groups during the premenstrual, menstrual and postmenstrual periods Figure 2 shows the comparison of the total MDQ scores. The mean total MDQ scores for the normal-sleep quality group and low-sleep quality group were 68.5 points (SD=22.4) and 79.8 points (SD=37.6), respectively, during the premenstrual phase (p=0.006, 95% CI: –16.000, 2.000). During menstruation, the mean total MDQ scores for the normal-sleep quality group and low-sleep quality group were 73.3 points (SD=34.2) and 93.7 points (SD=40.6), respectively (p<0.001, 95% CI: –29.000, 11.000). The mean total MDQ scores in the postmenstrual phase were 51.2 points (SD=24.6) in the normal-sleep quality group and 60.2 points (SD=33.0) in the low-sleep quality group (p=0.005, 95% CI: –6.000, 0.000). ![Figure 2](http://bmjopen.bmj.com/https://bmjopen.bmj.com/content/bmjopen/15/2/e093197/F2.medium.gif) [Figure 2](http://bmjopen.bmj.com/content/15/2/e093197/F2) Figure 2 Comparison of Menstrual Distress Questionnaire (MDQ) total scores. Figure 3 presents the results of the comparison of MDQ subscale scores during the premenstrual phase. The mean MDQ subscale scores in the normal-sleep quality group and low-sleep quality group of the various items were as follows: pain, 12.8 points (SD=6.6) and 15.1 points (SD=8.0), respectively (p=0.016, 95% CI: –3.000, 0.000); water retention, 10.0 points (SD=5.0) and 11.0 points (SD=5.2), respectively (p=0.091, 95% CI: –2.000, 0.000); automatic reaction, 5.5 points (SD=2.9) and 6.5 points (SD=4.0), respectively (p=0.050, 95% CI: 0.000, 0.000); negative affect, 15.8 points (SD=9.2) and 17.9 points (SD=10.0), respectively (p=0.025, 95% CI: –3.000, 0.000); concentration, 12.8 points (SD=7.0) and 15.7 points (SD=8.5), respectively (p<0.001, 95% CI: –3.000, 0.000); and behavioural change, 11.6 points (SD=6.6) and 13.6 points (SD=7.3), respectively (p=0.013, 95% CI: –3.000, 0.000). ![Figure 3](http://bmjopen.bmj.com/https://bmjopen.bmj.com/content/bmjopen/15/2/e093197/F3.medium.gif) [Figure 3](http://bmjopen.bmj.com/content/15/2/e093197/F3) Figure 3 Comparison of Menstrual Distress Questionnaire (MDQ) subscale scores: premenstrual. Figure 4 shows the results of the comparison of MDQ subscale scores during menstruation. In the normal-sleep quality group and low-sleep quality group, the mean MDQ subscale scores of the various items were as follows: pain, 15.4 points (SD=7.6) and 19.8 points (SD=8.6), respectively (p<0.001, 95% CI: –7.000, –2.000); water retention, 9.3 points (SD=4.6) and 11.1 points (SD=5.2), respectively (p=0.002, 95% CI: –3.000, –1.000); automatic reaction, 6.2 points (SD=3.7) and 7.8 points (SD=4.6), respectively (p<0.001, 95% CI: –1.000, 0.000); negative affect, 15.6 points (SD=8.7) and 20.2 points (SD=10.6), respectively (p=0.025, 95% CI: –6.000, –2.000); concentration, 13.8 points (SD=7.7) and 18.3 points (SD=10.2), respectively (p<0.001, 95% CI: –5.000, –1.000); and behavioural change, 13.0 points (SD=6.9) and 16.6 points (SD=7.7), respectively (p<0.001, 95% CI: –5.000, –2.000). ![Figure 4](http://bmjopen.bmj.com/https://bmjopen.bmj.com/content/bmjopen/15/2/e093197/F4.medium.gif) [Figure 4](http://bmjopen.bmj.com/content/15/2/e093197/F4) Figure 4 Comparison of Menstrual Distress Questionnaire (MDQ) subscale scores: during menstruation. Figure 5 provides the results of the comparison of MDQ subscale scores in the postmenstrual phase. In the normal-sleep quality group and low-sleep quality group, the mean of the MDQ subscale scores for the items is as follows: pain, 9.9 points (SD=6.0) and 11.4 points (SD=7.2), respectively (p=0.027, 95% CI: –1.000, 0.000); water retention, 6.8 points (SD=4.0) and 7.3 points (SD=3.9), respectively (p=0.086, 95% CI: –1.000, 0.000); automatic reaction, 4.9 points (SD=2.1) and 5.7 points (SD=3.4), respectively (p=0.072, 95% CI: 0.000, 0.000); negative affect, 11.4 points (SD=6.3) and 13.2 points (SD=8.0), respectively (p=0.011, 95% CI: 0.000, 0.000); concentration, 10.2 points (SD=4.2) and 12.8 points (SD=7.4), respectively (p<0.001, 95% CI: –1.000, 0.000); and behavioural change, 8.1 points (SD=4.6) and 9.8 points (SD=6.1), respectively (p=0.005, 95% CI: –1.000, 0.000). ![Figure 5](http://bmjopen.bmj.com/https://bmjopen.bmj.com/content/bmjopen/15/2/e093197/F5.medium.gif) [Figure 5](http://bmjopen.bmj.com/content/15/2/e093197/F5) Figure 5 Comparison of Menstrual Distress Questionnaire (MDQ) subscale scores: postmenstrual. ### Multiple logistic regression analysis To show the associations of sleep quality with the MDQ subscales, multiple logistic regression analysis in the crude model was performed (table 2). The MDQ concentration scores during the premenstrual period (β=0.068; p=0.034; OR 1.070; 95% CI: 1.005 to 1.140), pain during menstruation (β=0.057; p=0.040; OR 1.059; 95% CI: 1.003 to 1.117) and concentration during the postmenstrual period (β=0.165; p=0.003; OR 1.179; 95% CI: 1.058 to 1.313) were significantly associated with sleep quality. View this table: [Table 2](http://bmjopen.bmj.com/content/15/2/e093197/T2) Table 2 Multiple logistic regression analysis for the association of sleep quality with Menstrual Distress Questionnaire subscales in the crude model Furthermore, to assess the relationship between sleep quality and MDQ subscales, multiple logistic regression analysis was conducted in the adjusted model (table 3). In the premenstrual phase, a significant relationship with sleep quality was identified for concentration (β=0.071; p=0.028; OR 1.073; 95% CI: 1.008, 1.143). During menstruation, a significant relationship with sleep quality was detected for pain (β=0.058; p=0.038; OR 1.059; 95% CI: 1.003, 1.118). The MDQ concentration score during the postmenstrual phase was significantly associated with sleep quality (β=0.164; p=0.003; OR, 1.178; 95% CI: 1.058, 1.312). View this table: [Table 3](http://bmjopen.bmj.com/content/15/2/e093197/T3) Table 3 Multiple logistic regression analysis for the association of sleep quality with Menstrual Distress Questionnaire subscales in the adjusted model ## Discussion The aim of this study was to investigate the relationship between sleep quality and perimenstrual symptoms among Japanese female students. The main findings of this study revealed that lower sleep quality was associated with increased severity of perimenstrual symptoms. Furthermore, among the MDQ components, significant associations with sleep quality were observed for pain during menstruation and concentration during the premenstrual and postmenstrual periods. The Japanese population is known to have poor sleep habits, and in particular, college students are prone to disrupting their sleeping habits.27 Therefore, confirming whether sleep quality is associated with perimenstrual symptoms among Japanese female students and identifying perimenstrual symptoms most strongly related to sleep quality are important. First, this study compares its results with previous research investigating the association between sleep quality and perimenstrual symptoms. In a study among female university students, comparing PSQI scores with and without dysmenorrhoea showed that the group with dysmenorrhoea had higher PSQI scores and lower sleep quality (p<0.05).28 In another study focusing on premenstrual syndrome (PMS), women with severe PMS had lower subjective sleep quality in the late luteal phase.29 As seen in previous studies, some investigations have explored the relationship between perimenstrual symptoms and sleep quality. However, no studies have definitively confirmed which symptoms are particularly relevant among the various perimenstrual symptoms. This study not only examined the association between perimenstrual symptoms and sleep quality but also identified which symptoms were most strongly associated with sleep quality during each menstrual cycle. By focusing on specific perimenstrual symptoms, such as pain during menstruation and concentration difficulties during the premenstrual and postmenstrual phases, this study provides a more detailed understanding of the relationship between sleep quality and perimenstrual symptoms. A previous study of female undergraduate and graduate students in Taiwan found that normal- or low-sleep quality was associated with the onset of perimenstrual symptoms, and 51.4% of female students were indicated to have normal-sleep quality (PSQI<6) and 48.6% indicated to have low-sleep quality (PSQI≥6).30 These results suggest a relationship between sleep quality and perimenstrual symptoms. In our study, the severity of perimenstrual symptoms was lower in the normal-sleep quality group than in the low-sleep quality group, which is similar to the results of the previous study.30 Moreover, 53.7% of the participants were classified into the normal-sleep quality group and 46.3% into the low-sleep quality group, suggesting no participant bias when investigating sleep quality compared with that in previous studies. The average MDQ scores in Japanese young women aged 18 years and older6 are 57.2 points in the premenstrual, 63.0 points in the menstrual and 42.5 in the postmenstrual periods. In the present study, the average MDQ total scores were 74.2 points in the premenstrual, 83.5 points in the menstrual and 55.8 in the postmenstrual periods, which were higher than those reported in the previous study.6 A higher percentage of female college students have severe perimenstrual symptoms,31 which may explain the relatively high MDQ total scores of our study. The MDQ total scores and several subscale scores were higher in the lower-sleep quality group than in the normal-sleep quality group during all the menstrual periods. The most likely explanation for the association between sleep quality and perimenstrual symptoms is the influence of melatonin. Melatonin, which is responsible for inducing sleep, decreases with low-sleep quality.32 It is also involved in reproductive functions and plays a role in regulating the levels of oestrogen and progesterone.33 Thus, the decrease in melatonin secretion due to low-sleep quality might have led to a disturbance in the regulatory mechanism of female hormone levels, which might have resulted in the higher severity of perimenstrual symptoms in the low-sleep quality group. However, these discussions are predominantly speculative since this was a cross-sectional study based on an online survey, making it impossible to measure melatonin secretion or variations. Multiple logistic regression analysis showed that the MDQ subscale during menstruation related to sleep quality was ‘pain’, suggesting a relationship between sleep and dysmenorrhoea. In dysmenorrhoea without organic disease, the cause of pain could be excessive uterine contractions caused by prostaglandins released from the menstrual blood and uterine mucosa during menstruation. It is possible that the low-sleep quality group had more pain during menstruation because the prostaglandin system is activated when adequate sleep is not achieved.34 The MDQ subscale in the premenstrual and postmenstrual periods related to sleep quality was ‘concentration’. Female hormone levels are associated with cognitive function. For example, the change in estradiol levels with the menstrual cycle causes changes in cognitive function such as memory.35 Additionally, rapid changes in hormone levels during pregnancy alter cognitive abilities.36 These findings indicate that changes in female hormone levels are involved in memory and other cognitive functions. As discussed earlier, decrease in sleep quality decreases the secretion of melatonin, which plays a role in regulating female hormones, suggesting that sleep quality may be linked to concentration, a perimenstrual symptom. Decreased sleep duration and long-term sleep deprivation are common in the Japanese modern society. In a previous study involving Japanese college students, the mean sleep duration on weekdays was 5.9 hours; approximately 16% of the participants were categorised as evening-type individuals and 56.1% felt sleepy during the day.27 This seemingly represents the unhealthy sleeping habits of Japanese students. Perimenstrual symptoms are commonly experienced by female college students.31 Based on the results of our study, which demonstrates a relationship between sleep quality and perimenstrual symptoms, the need to improve sleep quality among Japanese female students is high. Sleep problems are caused by the blue light emitted from mobile phones and personal computers,37 humidity in the bedroom, bedding, background noise, human voices, lighting, etc.38 Particularly, the age group targeted in this study is one where smartphone usage is prevalent, making the issue of blue light exposure an important concern. About 2 hours before bedtime, the secretion of melatonin, a hormone that promotes sleep, begins. Exposure to light or the use of smartphones during this period, which emits blue light, has been reported to suppress the secretion of melatonin. This suppression disrupts the sleep-wake cycle, causing a delay in sleep onset and hindering the ability to fall asleep.39 Consequently, minimising blue light exposure from smartphone use at night could be a beneficial intervention. However, considering contemporary trends, it would be challenging to propose restrictions on smartphone use for students. Previous studies have demonstrated that regular aerobic exercise, such as walking or cycling, can enhance sleep quality by regulating circadian rhythms and decreasing sleep onset latency. Based on the results of a study by Lu in 2023, aerobic exercise significantly improved sleep quality in a sample of 719 college students, with a regression coefficient of −0.37 (p<0.001), as determined by regression analysis.40 Additionally, optimising the sleep environment, such as using comfortable bedding and controlling room temperature, has been linked to better sleep quality and efficiency. In a study by Bert *et al*, it was found that switching to a new bedding system significantly improved sleep quality and comfort, with improvements becoming more prominent over time.41 These findings suggest that the use of appropriate bedding could be an important factor in enhancing sleep quality. Along with reducing blue light exposure, such interventions may offer effective strategies for improving sleep among young adults. The present study had some limitations. First, the causal relationship between sleep quality and perimenstrual symptoms was not clarified. Second, the menstrual cycle at the time the participants completed the questionnaire was not considered, rendering this survey a cross-sectional one. However, the indicators used in this survey were established and confirmed to have no problems as retrospective formulas.22 Third, since this was a retrospective study, recall bias might have occurred during the recall of perimenstrual symptoms and sleep conditions in each menstrual period. To minimise recall bias, respondents were asked to respond to items related to sleep conditions and perimenstrual symptoms within the last month. Fourth, the survey used a snowball sampling method, raising questions about the potential lack of randomness and the representativeness of the sample in terms of individual status. Although the survey was broadly disseminated to mitigate regional or demographic biases, the snowball sampling approach may have introduced selective bias as participants likely shared the questionnaire with individuals possessing similar characteristics. A fifth limitation of this study is the relatively low response rate of 43.1% for the online survey. Although the questionnaires were distributed without geographical limitations, these fourth and fifth limitations may indicate particular characteristics of the respondents. As such, the results should be interpreted cautiously, and future studies with higher response rates and more representative samples are necessary to confirm these findings. Finally, the secretion of melatonin and other body hormones was not measured. Measuring these variables could yield objective data to enhance the understanding of the physiological mechanisms underlying the relationship between sleep quality and perimenstrual symptoms. Given these limitations, future research should focus on conducting longitudinal or experimental studies to explore the causal relationships between sleep quality and perimenstrual symptoms. Expanding the sample size to incorporate a more diverse population is essential, accounting for factors such as lifestyle, education level and other characteristics that could influence the results. Additionally, incorporating objective measurements of sleep and hormonal levels, such as melatonin secretion, would provide clearer insights into the physiological mechanisms involved. These steps would bolster the validity and generalisability of future findings. We examined the association between sleep quality and perimenstrual symptoms among Japanese female students who were divided into normal- and low-sleep quality groups based on the cut-off values of the PSQI-J. The low-sleep quality group had higher total MDQ scores and several subscale scores compared with those of the normal-sleep quality group during the premenstrual, menstrual and postmenstrual periods. In addition, multiple logistic regression analysis revealed that among the various menstrual symptoms, ‘concentration’ during the premenstrual and postmenstrual periods and ‘pain’ during menstruation were most strongly related to sleep quality. These results show that low-sleep quality may be associated with worsening perimenstrual symptoms and suggest the importance of considering and addressing these relationships in the management of women’s health issues. ## Data availability statement Data are available upon reasonable request. ## Ethics statements ### Patient consent for publication Not applicable. ### Ethics approval This study conformed to the guidelines of the Declaration of Helsinki and was approved by the Ethical Committee for Epidemiology, Hiroshima University (E-3791). Participants gave informed consent to participate in the study before taking part. ## Acknowledgments We thank the Graduate School of Biomedical and Health Sciences, Division of Integrated Health Sciences, Hiroshima University, for their cooperation in designing the study, as well as the female students who cooperated in distributing the questionnaires and answering the questions. ## Footnotes * Contributors The study was designed by SO, NM, TT, RM, MK, SA, TN and KN. Original drafting, reviewing and editing of the manuscript were performed by SO, TT and RM. The methodology was designed by SO, TT and RM. Formal analysis was performed by SO. The research was supervised by YU. All authors read and approved the final manuscript. SO is the guarantor. * Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors. * Competing interests None declared. * Patient and public involvement Patients and/or the public were involved in the design, or conduct, or reporting, or dissemination plans of this research. Refer to the Methods section for further details. * Provenance and peer review Not commissioned; externally peer reviewed. * Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. 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