Baskadia

A 2023 study that looked at how characteristics connected to the metabolic syndrome affected the quality of sleep-in premenstrual syndromes included 307 premenopausal women. The results showed that the women with PMS had lower quality sleep, higher levels of anxiety, and higher levels of sadness. Only women with PMS demonstrated significant changes in metabolic syndrome (MetS) characteristics associated to sleep quality when categorised into groups depending on their condition. In comparison to those who slept well, poor sleepers with PMS had greater waist circumferences and higher diastolic blood pressure. Compared to good sleepers, those with PMS who had poor sleep were three times as likely to be obese in the abdomen. Additionally, compared to good sleepers, PMS sufferers consumed almost three times as much alcohol. These patterns were not observed in women without PMS, indicating that lifestyle decisions and sleep quality had a major influence on MetS variables in PMS-affected women(14).

 A comprehensive analysis of 35 papers investigating the relationship between menstruation disorders and sleep revealed that dysmenorrhea and premenstrual syndrome (PMS) were linked to a number of different sleep-related problems. These included having trouble falling and staying asleep (Efficiency), having trouble falling asleep and staying asleep (Satisfaction), and having short sleep durations (Duration). Poor sleep quality, trouble falling asleep, and short sleep duration have also been related to abnormal menstrual cycles and severe menstrual flow. None of the research, though, looked into when people sleep(15).

A study on the impact of social media addiction on premenstrual syndrome and sleep quality involved 884 female students enrolled in a public university's Health Sciences Faculty. The "Personal Information Form," "Social Media Addiction Scale (SMAS)," "Premenstrual Syndrome Scale (PMSS)," and "Pittsburgh Sleep Quality Index (PSQI)" were the devices used to gather data. For statistical evaluation, descriptive statistics, linear regression analysis, and Pearson correlation analysis were employed.  The students' average age was 20.40±1.65, and the menarche age was 13.42±1.60. For PMSS, the average total score was 129.57±37.75, for SMAS, it was 12.93±4.84, and for PSQI, it was 13.22±2.04. SMAS and the overall PMSS and PSQI scores showed a favourable link, according to the correlation analysis (r=.325, p=.000; r=271, p=.000). Furthermore, a one-unit change in the social media addiction scale score results in a positive rise of.325 units (β) on the premenstrual syndrome scale's total score and a positive increase of 0.444 units (β) on the PSQI's total score, according to the regression analysis. t has been discovered that social media addiction is a significant factor in elevating symptoms of premenstrual syndrome and reducing the quality of sleep(16).

In Gyeonggido, South Korea, 519 high school girls between the ages of 15 and 18 participated in a cross-sectional survey study in 2021 when the area was under COVID-19 lockdown. The Cox menstrual symptom scale (CMSS) and the visual analogue scale (VAS) were used to measure the severity of menstrual pain and symptoms, respectively. The premenstrual symptoms screening tool (PSST) was used to evaluate premenstrual syndrome. The Pittsburgh Sleep Quality Index (PSQI) was used to evaluate sleep. Covariates comprising stress and established risk factors for dysmenorrhea, such as lifestyle and menstrual features, were evaluated the premenstrual symptoms screening tool (PSST) was used to evaluate premenstrual syndrome. The Pittsburgh Sleep Quality Index (PSQI) was used to evaluate sleep. The recognized dysmenorrheal risk factors About 68% of girls reported sleeping for seven hours or fewer during the epidemic, and about 60% said their sleep was of poor quality. Furthermore, 34% of participants woke up later than 8AM, and 64% of participants went to bed later than 1AM. The VAS (P = 0.05), CMSS severity and frequency (both P < 0.01), and PSST symptom (P < 0.01) were all significantly impacted by late bedtime. A late night had an impact on PSST function (P < 0.05), CMSS severity (P < 0.05), and PSST symptom (P = 0.05). But after adjusting for variables, these effects' significance vanished. Less than five hours of sleep had an impact on PSST symptoms (P < 0.001) and CMSS frequency (P < 0.05). The significance of the effect on PSST symptom persisted (P < 0.05) even after adjusting for variables. After adjusting for covariates, the frequency and severity of CMSS as well as PSST symptoms were significantly impacted by general sleep quality and PSQI components, such as subjective sleep quality, sleep latency, sleep disturbance, use of sleeping medication, and daytime dysfunction (P < 0.05, P < 0.01, or P < 0.001). The results of the multiple regression analysis showed that the most significant risk factor for premenstrual syndrome and dysmenorrhea among the aspects of sleep was sleep quality(17).

A 2020 Chinese study examined the relationship between menstruation issues and sleep disturbances among female university students. In this study, 1006 female university students made up a convenience sample. The Pittsburgh Sleep Quality Index and the Insomnia Severity Index were used to measure the amount of sleep, the quality of the sleep, and the symptoms of insomnia. The study included a standardized questionnaire to evaluate the menstrual features and demographics of the subjects. The findings demonstrated that those with sleep disturbances had significantly higher prevalence rates of period discomfort, premenstrual syndrome, heavy menstrual bleeding, menstrual flow length ≥ 7 days, and irregular menstrual cycles (all p < 0.05) than those without sleep disturbances. Poor sleep quality and symptoms of insomnia were found to be significantly associated with menstrual flow length of less than seven days (OR = 1.81, 95% CI = 1.23–2.68, OR = 1.67, 95% CI = 1.13–2.45), period pain (OR = 1.55, 95% CI = 1.02–2.35, OR = 1.56, 95% CI = 1.02–2.37), and premenstrual syndrome (OR = 1.71, 95% CI = 1.30–2.24, OR = 1.93, 95% CI = 1.46–2.56). Furthermore, there was a substantial correlation between heavy monthly bleeding and poor sleep quality (OR = 1.75, 95% CI = 1.12–2.72), and a significant correlation between symptoms of insomnia and irregular menstrual cycles (OR = 1.36, 95% CI = 1.02–1.80). Short sleep duration (≤ 6 hrs) was linked exclusively to premenstrual syndrome, though(18).

A study included 768 reproductive-age Egyptian women who provided self-reported information in a questionnaire. The three components of this questionnaire were the Pittsburg Sleep Quality Index (PSQI), the premenstrual syndrome scale (PMSS), and the demographic data sheetThe main results included the frequency, intensity, and relationship between PMS and PSQI with regard to sleep quality. Secondary outcomes were participant demographics and how these affected the PMS and PSQI.  Ninety-five percent of the individuals reported having PMS, with symptoms varying from moderate to extremely severe. A noteworthy positive connection (p<0.01) was observed between PSQI and PMS. When compared to the demographic variables, PMS did not correlate (P>0.05), and the only significant differences were seen in body weight and age with respect to PSQI(19)

Research of nurses working in private hospitals in Bangkok, Thailand. This study employed a cross-sectional study design. Participants were selected from among 209 female nurses working in a private hospital who reported having a regular menstrual cycle. The subjects were given the normal self-report questionnaire. The Premenstrual Symptoms Screening Tool (PSST) and the Pittsburgh Sleep Quality Index (PSQI) were accessed in Thai, respectively, to measure premenstrual syndrome and sleep quality. Using the Chi-square test, the relationships between the variables and the quality of sleep were examined. Using binary logistic regression, the adjusted odd ratio of PMS on inadequate sleep quality was determined. Among registered nurses, the average age was 31.38 (±5.35) years. Eighty-two.9% of them had a normal stress level, and 78.9% of them were single. Sixty-five percent of the nurses had been working alternating shifts, including nights. 66.5% of nurses had a poor sleep quality index (PSQI > 5). 7.7% of nurses were premenstrual syndromed. The most common symptoms of premenstrual syndrome that were described were physical symptoms (48.30%) and overeating/food craving symptoms (41.60%). Poor sleep quality was not significantly correlated with premenstrual symptoms. Almost all premenstrual syndrome symptoms were associated with a poor quality of sleep (OR adjusted >1), according to binary logistic regression, even if statistical significance was not reached(20).

A cross-sectional study on Association between Premenstrual Syndrome and Quality of sleep among hostilities students. 137 hostile females participated in a study that was carried out utilising a non-probability convenient sampling method. Students from various universities in Lahore who were staying in hostels provided the data. The Pittsburgh Sleep Quality Index (PSQI) questionnaire was used to assess sleep quality, while the Premenstrual Syndrome Scale was employed to measure PMS. The participants' average age was 22.31±1.684 years. Twenty was the minimum age and twenty-five was the maximum. Twenty (14.6%) have moderate symptoms, twenty (59.1%) have mild symptoms, and twenty (17.5%) have severe premenstrual syndrome symptoms. In this study, 27.1% of participants without PMS reported having good sleep quality, compared to 72.9% of females with PMS who reported having poor sleep quality (p-value <0.001)(21).

An investigation into the health-related quality of life of teenagers with premenstrual syndrome Included in the study was a sample of teenage schoolgirls, ages 14 to 19. Premenstrual disorders were identified using the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) and the International Classification of Diseases (ICD-10). The SF-36, or Short Form Health Survey, was used to measure health-related quality of life. The results were compared across study sample subgroups and descriptive analysis was performed. A total of 602 female pupils were examined. At least one premenstrual symptom was mentioned by every student. Of these, 224 (37.2%) satisfied the premenstrual dysphoric disorder (PMDD) diagnostic criteria. When comparing the SF-36 ratings of female students with and without PMDD, all measures showed significant differences (P < 0.001), with the exception of physical functioning (P = 0.274). The roles of emotional, physical, social, and physical pain were where these variations were most noticeable(22).

A study conducted in USA in 2012 involving 18 women with severe premenstrual syndrome (PMS) and 18 controls with minimal symptoms found that women with PMS reported poorer subjective sleep quality during the late-luteal phase compared to the follicular phase, despite no corresponding objective changes in sleep quality. Women with PMS exhibited more slow-wave sleep and slow-wave activity than controls in both phases and had higher levels of anxiety, depression, fatigue, and perceived stress, which worsened in the late-luteal phase. Both groups showed similar menstrual-phase effects on sleep, including increased spindle frequency activity and shorter REM sleep episodes in the late-luteal phase. In women with PMS, poorer subjective sleep quality was strongly correlated with higher anxiety and more perceived nighttime awakenings. These findings suggest that while women with PMS perceive poorer sleep quality, this perception is influenced by anxiety rather than actual sleep disturbances, indicating that better management of mood symptoms may improve their subjective sleep quality(23).

Study carried out in Brazil 49.9% of the 642 students had premenstrual dysphoric disorder (PMDD), 23.3% had mild PMS, and 26.6% had PMS. Most of the students were in their 18–24-year age range, engaged in regular physical activity, and had regular menstrual cycles. A statistically significant difference was noticed between the students who did not have and those who had mild or PMDD in relation to the physical and mental domains of the WHOQOL-Bref scale (p < 0.001). Additionally, there was a difference observed in the social ties (p = 0.001) and environmental domains (p = 0.009) between the students without PMS and those with mild PMS(1).

A study in Turkey involving 1,008 university students found that 36.3% had premenstrual syndrome (PMS). The median age of students with PMS was slightly higher (21 years) than those without PMS. Most students lived in dormitories (72.1%) and had an average family income (76.5%). Around 8.9% of students were smokers, and 8.6% were overweight or obese. The average age at menarche was 13.3 years, the menstrual cycle length averaged 28.7 days, and menstrual flow lasted about 6.1 days. Dysmenorrhea (painful periods) affected 70.6% of students. Students with PMS scored lower on all quality of life domains measured by the SF-36 questionnaire compared to those without PMS(9).

According to the findings of a study titled "The Effect of Premenstrual Syndrome on Quality of Life in Adolescent Girls," teenagers with PMS scored lower on all SF-36 scales (P<0.001) when compared to their healthy counterparts. With the exception of vitality and mental health, there was no discernible variation in the SF-36 quality of life measures across different PMS severity levels (P>0.05). On the other hand, SF-36 scores for mental health and vitality showed a statistically significant difference between severe and mild PMS (P=0.002)(24).

Among Isra University students a study was conducted in which convenience sampling was used to select unmarried medical students, ages 18 to 25, who had regular menstrual periods for the previous six months, for a study on the frequency, intensity, and effects of premenstrual syndrome among medical students. For two potential cycles, data pertaining to PMS was gathered on the daily record of severity of problems (DRSP). After obtaining participants' informed consent, health-related quality of life data was gathered using the medical outcome study Short Form 36 (Sf – 36). The mean age of the 172 study participants was 21.2 + 1.9 years. Ninety-nine (51%) of the females who fit the criteria for PMS recording to ICD-10 had mild PMS, followed by moderate PMS in 26, moderate PMS in 29, and severe PMS in 10. Using the DSM-IV criteria, ten girls (5.8%) were diagnosed with premenstrual dysphoric disorder (PMDD). Anger, irritability, anxiety, fatigue, difficulty concentrating, mood swings, and somatic symptoms including breast tenderness and overall body discomfort were the most common symptoms, along with significant impairments in social life, activities, and work efficiency/productivity. Premenstrual syndrome was substantially correlated with dysmenorrhea (p=0.003) and a family history of premenstrual syndrome (p < 0.01), according to univariate and multivariate analyses. The afflicted group exhibited a considerably lower Sf – 36 score on the Mental Component Summary (MCS) and Physical Component Summary (PCS)(25).

A cross-sectional study was conducted on 246 women who were referred to health centres in Yazd. They were chosen randomly. The premenstrual syndrome screening test and the quality-of-life questionnaire SF36 were used as data collection instruments. The collected data were examined using SPSS18.0, which included the SF-36 subscales Kruskal-Wallis and Mann-Whitney tests for comparison groups. Total of 102 samples (41.5%) exhibited premenstrual syndrome (PMS), 20 samples (8.1%) had diagnostic features for premenstrual dysphoric disorder (PMDD), and 124 samples (50.4%) belonged to the general population (GP) group. With the exception of physical function in other quality of life components, comparison groups using the Kruskal-Wallis test on SF-36 subscales revealed a significant difference (p<0.05) between PMS and PMDD groups and non-clinical individuals. Women with PMDD reported a low health-related quality of life, as assessed by the SF-36, taking into account the Mann-Whitney test. Particularly when it came to role constraint and emotional issues, women with PMS and PMDD scored lower on the mean scale. They concluded that premenstrual symptoms severely impact quality of life, particularly in the area of role limitation and emotional issues(26).

An investigation into Turkish nursing students A correlational design was employed to gather data from 183 nursing students at Artvin Çoruh University's Health School. Students who volunteered to participate filled out a questionnaire that included the Pittsburgh Sleep Quality Index (PSQI), Menstrual Attitude Questionnaire (MAQ), Premenstrual Syndrome Scale (PMSS), and sociodemographic variables. Ages were 19.9 (1.8) on average. The results of the study showed that there was a negative significant association (r=-0.317; P<0.01) between the PMSS score and the overall mean score of MAQ, and a positive significant correlation (r=0.306; P<0.001) between the PMSS score and mean scores of PSQI. Similarly, the total score of PMSS was strongly affected by the total scores of MAQ (β = -27.455; P = 0.001) and PSQI (β = 5.412; P<0.001), according to multiple linear regression analysis. They came to the conclusion that negative views towards menstruation and poor sleep quality are linked to the severity of PMS symptoms. Finding coping mechanisms for PMS and educating young girls on the subject may improve the quality of their lives in the future(27).

According to Mauri et al. premenstrual syndrome (PMS) patients and women in the general population both frequently experience sleep difficulties during this time. A clinic sample of PMS patients provided reports on the Post-Sleep Inventory, while samples from the general public were divided into non-clinic groups based on their scores on the Premenstrual Tension Syndrome Self-Rating Scale, with and without premenstrual disruption. The patients consistently reported higher levels of disturbance than either of the other two groups. Patients with PMS reported having bad nightmares, waking up throughout the night, not waking up at the scheduled time, feeling exhausted in the morning, and having more mental activity during the night and when they woke up. With an aggregate accuracy of 82%, the three groups could be reliably discriminated against on this basis. Premenstrual disorders sometimes include sleep difficulties, which call for specialised therapeutic care and more research(28).