Levels and Factors of Premenstrual Syndrome (PMS) among Female College Students

Background: Premenstrual syndrome (PMS) affects women’s physical and mental health. Depression, stress, sleep disturbance, and eating attitude problems have been known to in�uence PMS. Furthermore, restrictions of daily life due to the COVID-19 pandemic have led to changes in sleep patterns and eating attitudes. Thus, it is necessary to closely examine how these factors affect PMS. This study aimed to examine the levels of PMS, stress, depression, sleep disturbance, and eating attitude problems among female college students who experience dysmenorrhea and determine the factors associated with PMS. Methods: A cross-sectional online survey design was conducted using a convenience sample of 143 female college students in C City, South Korea. Differences in participants' level of PMS according to physical health variables (e.g., smoking, water intake, menstrual pain intensity) and psychological issues (i.e., stress, depression, sleep disturbances, and eating attitude problems) were assessed with independent sample t-tests and one-way ANOVAs. Correlational analyses between these variables were also conducted. Additionally, multiple regression was performed to identify the factors in�uencing PMS. Results: PMS severity was between normal (27.3%) and premenstrual dysphoric disorder (PMDD) (72.7%). PMS was associated positively with depression (r=.284, p=001), stress (r=.284, p=.001), sleep disturbance (r=.440, p< .001), and eating attitude problems (r=.266, p=.001). Additionally, menstrual pain intensity ( β =.204), sleep disturbances ( β =.375), and eating attitude problems ( β =.202) were found to in�uence PMS. The regression model was signi�cant (F=16.553, p<.001) with an explanatory power of 24.7%. Conclusions: Considering the in�uencing factors of PMS identi�ed in this study, interventions for participants experiencing PMS should be made. We propose that further study should be conducted to examine whether the severity of PMDD changes according to menstrual pain, the pattern and degree of its change, and the paths through which sleep quality and eating attitude problems affect PMS


Introduction
Premenstrual syndrome (PMS) is a combination of more than 200 complex symptoms including physical symptoms (e.g., breast tenderness and abdominal bloating and cramping), behavioral symptoms (e.g., fatigue, sleep disturbances, and cravings), and emotional symptoms (e.g., irritability, anger, and anxiety) [1], which develop approximately 2-10 days before the period and disappear just before or shortly after menstruation begins [2]. Even though the etiology of PMS is unclear, a wide variety of factors seem to come into play, including interactions between biological factors (e.g., hormonal imbalance and neurotransmitter changes) [3] and psychosocial factors (e.g., attitude toward menstruation and stress) [4] as well as routine health behaviors (e.g., exercise, smoking, drinking, sleep duration, diet, and nutrient intake) [1]. PMS is experienced by 99% of Korean women of reproductive age (15 to 49 years), and 13.6 to18.6% of them are diagnosed with premenstrual dysphoric disorder (PMDD) [5], which is included in the depressive disorders chapter of the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition  [6]. Speci cally, women 21-25 years old (college students) have a higher incidence of PMS than high school students and middle-aged women [7]. Although 28.0% of female university students experience severe PMS-induced stress [8] and disturbances in everyday life, they rarely receive professional care [9].
Women affected by PMS easily succumb to negative emotions and have di culties controlling emotions [10]. Among such negative emotions, depression is known to have the highest in uence on PMS [11].
Because women at risk of depression tend to have a high likelihood of PMS, it is necessary to assess the risk of depression in women with PMS [12]. In addition, the onset of menstruation itself can act as a stressor for women [9], and, given that a higher stress level is associated with a higher PMS level [13], PMS should be considered together with psychological and emotional problems experienced by women.
Some changes arising from restrictions of daily life due to the COVID-19 pandemic have also led to changes in sleep patterns [14]. Generally, women experiencing PMS are susceptible to sleep disturbances due to hormonal changes associated with the menstrual cycle [15]. They experience di culties in all aspects of sleep, including sleep duration, quality, latency, maintenance, and wake-up time compared with women unaffected by PMS [15]. In fact, a much higher proportion of women with PMS suffer from poor sleep quality than women without PMS (75.6% vs. 58.8%) [16], and women with sleep disorders have a 1.7-fold risk of PMS compared to women without sleep disorders [17], demonstrating a close association between PMS experience and sleep quality.
Eating attitude problems have also been associated with PMS [18]. Differences in appetite and eating habits are observed between healthy women and women with PMS [19]. In particular, PMS among female college students is signi cantly associated with both eating attitude problems and depression [20]. In addition, during the COVID-19 pandemic, hospitalizations for eating behavior-related problems, such as anorexia nervosa [21] and other eating disorders [22], have increased. Therefore, the relationship between the eating habits and PMS in female college students should be paid attention to.
In this study, we examine the levels of PMS, stress, depression, sleep disturbances, and eating attitude problems in female college students who experience dysmenorrhea and determine factors associated with PMS. We aim to provide basic data to set up nursing intervention programs designed to prevent and counter PMS more e ciently.

Participants
Participants who met the following inclusion criteria were recruited: unmarried female college students in their 20s who experienced dysmenorrhea, understood the purpose of this study, and were able to respond to the questionnaire survey. They were recruited based on the research ndings that the more severe the dysmenorrhea, the more severe the PMS symptoms [23] and that 90.2% of female college students experience weak to strong dysmenorrhea [24]. Those who experienced childbirth through a common-law relationship or had comorbid physical or mental illnesses other than dysmenorrhea were excluded. The minimum sample size of this study estimated using the G*Power 3.1 program was 153 participants for power .80, effect size .15, and signi cance level .05 with 19 predictors. Considering a dropout rate of 10%, the online questionnaire survey remained open until the number of respondents reached 170, and after removing the respondents who gave uniform answers to all items, data from 143 respondents were nally used for analysis in this study.

Data Collection
A recruitment poster explaining the purpose of the research, data collection and processing procedures, and withdrawal from participation was displayed on Dankook University's online open bulletin board (for event announcement) from September 1 to 19, 2021. Those interested in participating in the study were requested to voluntarily consent to participate in the survey and allow the use of personal information for research purposes by checking the corresponding boxes and were then led directly to the URL for the online questionnaire. Those who completed the questionnaire were given a small token as appreciation.
Research tools

1) PMS
The level of PMS was measured using the Shortened Premenstrual Assessment Form (SPAF) developed by Allen et al. [25] and translated by Lee et al. [26]. The SPAF consists of 10 items eliciting information on the level of each of the PMS symptoms that develop during the premenstrual week. Each item is rated on a 6-point Likert scale (1 = strongly disagree, 6 = strongly agree), with the total score ranging from 10 to 60 points, where a higher score indicates more severe PMS symptoms. The cut-off of 27 points was used to distinguish between PMDD and non-PMDD cases. The Cronbach's α value was .91 in the study of Lee et al. [26] and .87 in this study.

2) Stress
The level of stress was measured using the Korean version of the Perceived Stress Scale (PSS) developed by Cohen et al. [27] and translated by Lee et al. [28]. This scale consists of 10 items, and each item is rated on a 4-point Likert scale (0 = almost never, 1 = sometimes, 2 = fairly often, 3 = very often). A higher total score indicates a higher level of perceived stress. Cronbach's α reliability coe cient was .82 in the study of Lee et al. [28] and .79 in this study, indicating good internal consistency of the scale.

3) Depression
Depression was measured using the Korean version of the Center for Epidemiologic Studies Depression Scale-Revised (K-CESD-R) originally conceived by Eaton et al. [29] and translated into Korean and validity-and reliability-tested by Lee et al. [30]. This tool consists of 20 items eliciting information on participants' weekly frequency of depression symptoms. Each item is rated on a 4-point Likert scale (0 = not at all or less than one day, 1 = 1-2 days, 2 = 3-4 days, 3 = 5-7 days or nearly every day for 2 weeks). The higher the total score, the higher the level of depression, with 0-20 points de ned as normal, 21-40 points as risk, and 41-60 points as high-risk groups. Cronbach's α reliability coe cient was .98 in the study of Lee et al. [30] and .91 in this study.

4) Sleep Disturbances
Sleep disturbances were measured using the General Sleep Disturbance Scale (GSDS) developed by Lee [31] and translated by Choi et al. [32]. This tool consists of 21 items asking for the frequency of sleep problems in the past week grouped into six factors: sleep onset, maintenance of sleep, quality of sleep, quantity of sleep, fatigue and alertness at work, and use of substances to help induce sleep. The total score ranges between 0 and 147 points, where higher scores indicate greater likelihood of sleep problems. The lowest Cronbach's α reliability coe cient was .75 in the GSDS developed by Lee [31] and .81 in this study.

5) Eating Attitude Problems
Eating attitude problems were measured using the Eating Attitudes Test-26 (EAT-26) developed by Garner et al. [33], with its Korean version standardized by Rhee et al. [34]. This tool comprises 26 items measuring diet-related problems clustered in four factors: self-control of eating and bulimic symptoms, preoccupation with being thinner, food preoccupation, and dieting. Each item is rated on a 4-point Likert scale (0 = never, 3 = always), with a higher scores indicating higher likelihood of eating attitude problems.
Based on a previous study [35], the total score range of 0-21 points is assessed as normal, 22-26 points as a possible eating disorder, and 27-78 as a severe disorder. Cronbach's α reliability coe cient of the Korean version standardization study with women was .81; that of this study was .83.
The level of dysmenorrhea was assessed with the Numeric Rating Scale (NRS), which resulted in a mean pain level of 6.73±2.16. Based on the pain assessment proposed by McCaffery et al.
The measurement and analysis of the variables for the participants' characteristics resulted in the following ndings: Signi cant differences in PMS were observed in BMI (F=3.535, p=.017), amount of menstruation ow (F=4.241, p=.016), and menstrual pain intensity (F=4.228, p=.016). In the post-hoc testing, however, only the menstrual pain intensity of 7-10 points (severe) was found to have a signi cantly higher PMS level than 1-3 points (mild) ( Table 1).

In uencing factors on PMS
Multiple regression analysis was performed by inputting the menstrual pain intensity, which showed posthoc differences among the participants' general characteristics and major variables (depression, stress, sleep disturbances, and eating attitude problems). In the analysis of multicollinearity between independent variables, the tolerance limit was greater than 0.1 (0.933-0.975) and the VIF was less than 10 (1.026-1.072), demonstrating that there was no problem of multicollinearity. As a results of multiple regression analysis, menstrual pain intensity (β=.204), sleep disturbances (β =.375), and eating attitude problems (β =.202) were found to have an effect on PMS. The regression model was signi cant (F= 16.553, p < .001) with an explanatory power of 24.7% (Table 4).

Discussion
In this study, we examined the levels of PMS, stress, depression, sleep disturbances, and eating attitude problems among female college students who experience dysmenorrhea and determined factors associated with PMS.
The mean pain intensity of dysmenorrhea experienced by the participants of this study was 6.73/10, and the majority (66.4%) of participants experienced severe pain of seven points or higher. In this study, menstrual pain intensity was identi ed as the primary factor affecting the level of PMS, which is consistent with ndings of previous research [37] and aligns with the nding that menstrual pain is a signi cant pathway to PMS [38]. The PMS measurement tool includes two items expressing pain, which can explain the high correlation between the level of PMS and the menstrual pain intensity. Moreover, the fact that menstrual pain intensity was identi ed as the rst determinant of the level of PMS-a complex syndrome combining physical, behavioral, and emotional symptoms-can be interpreted as meaning that various symptoms of PMS are closely related to pain. According to a previous study [39], Korean female college students perceive menstruation as a factor that weakens their physical and psychological health more markedly than their U.S. counterparts, which is the reason behind their more intense pain reports. Therefore, it is necessary to understand dysmenorrhea as more than a mere physical symptom (i.e., dysmenorrhea is psychological as well as physical), reconsider menstruators' perceptions of menstruation, and seek out diverse factors related to PMS. Moreover, it is necessary to establish appropriate coping strategies for each of those factors, going beyond medication or palliative treatment.
All participants in this study experienced dysmenorrhea. Even taking this into account, the nding that the majority (n = 104, 72.7%) of them experienced PMDD contrasted with prior ndings that 85% of adolescents experience PMS, of which 38% were classi ed as PMDD [40]. An accurate clinical diagnosis of PMDD requires daily prospective symptom assessment [26]. Therefore, it is necessary to guide the patient so that they can receive active management with an appropriate understanding of unpleasant premenstrual symptoms.
In this study, stress and PMS levels were positively correlated, which is consistent with previous research [41]. However, stress was not con rmed as a determinant of PMS, unlike a previous study that identi ed stress as a determinant of PMS [13]. Changes in hormonal levels throughout the menstrual cycle may affect sensitivity to stress, intensifying PMS symptoms by responding more intensely to stressors, particularly in the premenstrual or luteal phase [42]. Moreover, because stress acts as a signi cant factor for irregular menstrual cycles, thereby affecting changes in menstrual function [43], it is important to include stress as a variable for PMS intervention. Intervention strategies are required to strengthen individuals' coping ability and protective factors against stress through an in-depth understanding of premenstrual emotional characteristics and negative emotion control strategies by college students themselves.
Whereas depression was positively correlated with the level of PMS, it was not con rmed as a determinant of PMS, which is partially consistent with the ndings of previous research [4]. Given that the level of PMS is a signi cant risk factor for depression [20] and that college students who experience PMS are more likely to experience depression compared to those who do not [20], it is necessary to assess the risk of depression [12]. PMS induces negative emotions due to hormonal changes and lasts for a short time, disappearing with the onset of menstruation. However, because symptoms appear repeatedly over a long time and are not uniform but accompanied by a wide variety of physical, emotional, and behavioral symptoms, healthcare professionals need to understand the correlation between college students' PMS experiences and emotional problems such as depression. They should prepare multifaceted interventional strategies capable of countering emotional problems more e ciently through preliminary assessments of depression severity and positive communication among family members.
However, sleep disturbance showed a positive correlation with PMS and was identi ed as the second determinant of PMS. This nding is similar to those of previous studies [44,45] that revealed correlations between PMS, sleep duration, and sleep quality [44,45] and identi ed unsatisfactory sleep quality as a determinant of PMS in female college students [46]. Our results also support the ndings in a previous study that women with PMS had a shorter sleep duration, needed a longer time to fall asleep, and had lower quality of sleep compared with women without PMS [47]. Sleep, a basic human need, is an essential factor for individuals to maintain good health and satisfaction, including physical, mental, social, and spiritual functions and overall quality of life [48]. Since the outbreak of COVID-19, infection control policies, such as online education and social distancing, have changed various aspects of psychological health (e.g., stress and depression) [49] as well as lifestyle (e.g., sleep problems) [50]. Changed lifestyle patterns, in particular, lowered sleep quality due to the use of digital media before bedtime [51]. Sleep will have to be considered an important variable in PMS intervention, and a quality sleep management strategy should focus more on sleep quality than on sleep duration.
Finally, more serious eating attitude problems were found to be associated with higher levels of PMS, and eating attitude problems were thus identi ed as the third determinant of PMS level. This nding is in line with that of a previous study in which eating attitude problems-measured with EAT-26, the same tool used in this study-were observed more frequently in adolescents with PMS than in those without it [52].
Speci cally, adolescents with PMS scored higher in emotional and uncontrolled eating behaviors. Moreover, a higher level of neurotic bulimia is more closely associated with moderate-to-severe PMS than no or mild PMS, with the highest level manifesting in cases diagnosed with PMDD, suggesting that the extent of eating attitude problems may differ depending on the premenstrual emotional state [53]. Given that PMDD is de ned as a more serious form of PMS, eating attitude problems may increase as PMS severity increases. Therefore, it is essential to meticulously examine the severity of PMS symptoms experienced by the participants and plan customized interventional strategies accordingly.
As limitations of this study, it may be noted that because the study analyzed data obtained through a cross-sectional survey conducted at one university, it cannot be extended to discussing the causal relationships between PMS and individual variables such as stress, depression, sleep disturbances, and eating attitude problems. Additionally, its results cannot be directly generalized to all female college students. Despite this limitation, this study is signi cant because it has successfully measured the level of PMS experienced by female college students who have dysmenorrhea and identi ed three determinants of PMS, including emotional factors (i.e., depression and stress) and lifestyle factors (i.e., sleep, diet, and exercise).

Conclusions
In this study, we examined the levels of PMS, stress, depression, sleep disturbances, and eating attitude problems among female college students who experience dysmenorrhea and determined factors associated with PMS. Menstrual pain intensity, sleep disturbances, and eating attitude problems were found to have an effect on PMS. Because PMS exacerbates in the late luteal phase of the menstrual cycle and is accompanied by predictable and periodic psychological and physical symptoms that are resolved with the onset of menstruation. Therefore, individuals should have a good understanding of their own menstrual pain patterns and be able to set up suitable coping strategies, such as exercise, alternative therapy, and painkiller medication. Furthermore, to minimize the experience of PMS symptoms and negative effects, individual coping strategies for emotional well-being should be sought, and effective interventions applied to help correct problems accompanying sleep and eating attitudes. We propose that further study should be conducted to examine whether the severity of PMDD changes according to menstrual pain, the pattern and degree of its change, and the paths through which sleep quality and eating attitude problems affect PMS. Availability of data and materials The datasets used and/or analyzed during the current study available from the corresponding author on reasonable request.

Competing interests
The authors declare that they have no competing interests. Authors' contributions MK designed of the study. IP collected data. MK, SY conducted the data analysis and wrote the manuscript. All authors drafted the paper approved the nal paper prior to submission.