Prevalence and associated factors of premenstrual syndrome among women of the reproductive age group in Ethiopia: Systematic review and meta-analysis.

INTRODUCTION: Premenstrual syndrome is a clinical condition characterised by the cyclic occurrence of physical and emotional symptoms, which can interfere with normal activity. It significantly affects the health-related quality of life and can result in decreased work productivity. The prevalence of premenstrual syndrome varies widely in different countries and different regions of the same country. Thus, this study was aimed to estimate the pooled prevalence of premenstrual syndrome and its associated factors among women in Ethiopia.
MATERIALS AND METHODS: Published studies searched from electronic databases such as PubMed/Medline, google scholars, HINARI, Science Direct, Cochrane Library, and EMBASE were used. All studies done among women of the reproductive age group in Ethiopia and reported in the English language were included. The current study was reported using Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Two authors extracted the data independently by using Microsoft excel extraction format and transported to STATA 14 software for analysis. I2 test was used to assess heterogeneity between the studies. A random-effect model was computed to estimate the pooled prevalence and associated factors of premenstrual syndrome. The prevalence and odds ratio with 95% confidence interval (CI) were presented using a forest plot.
RESULTS: After careful screening of 33 studies, nine studies were included in our systematic review and meta-analysis. The pooled prevalence of premenstrual syndrome in Ethiopia was found to be 53% (95% CI: 40.64, 65.36). Subgroup analysis by university versus high school showed a pooled prevalence of 53.87% (95% CI: 40.97, 67.60) and 56.19% (95% CI: 6.80, 105.58), respectively. The pooled odds ratio shows that age at menarche, menstrual pattern and hormonal contraceptive use had no statistically significant association with premenstrual syndrome.
CONCLUSION: More than half of the women under reproductive age group were experiencing premenstrual syndrome in Ethiopia.

Introduction

The American College of Obstetricians and Gynecologists (ACOG) defined premenstrual syndrome (PMS) as a clinical condition characterised by the cyclic occurrence of physical and emotional symptoms unrelated to any organic disease that appear during the five days before menses and ends at four days after onset of menses in three consecutive cycles with sufficient severity that interfere with normal activity [1].

Premenstrual syndrome is diagnosed based on timing of the symptoms. The diagnosis starts with women’s experience of at least one of affective or somatic symptoms before 5 days of menses in three prior menstrual cycles which is relieved with menstruation. The affective symptoms are depression, angry outbursts, irritability, anxiety, confusion, social withdrawal, and somatic symptoms are breast tenderness, abdominal bloating, headache, swelling of extremities. Premenstrual syndrome can only be proven after exclusion of other diagnosis that may better explain the symptoms. Again the symptoms should be confirmed by two prospective cycles with impairment of some facet of women’s life [1].

The prevalence of premenstrual syndrome varies in different countries. For instance, the prevalence of premenstrual syndrome was reported as 12.2% in France [2] and 98.2% in Iran [3]. The global prevalence of premenstrual syndrome is 47.8% (95% CI: 32.6–62.9) [4].

Although the exact cause of premenstrual syndrome is not known, it is believed to be triggered by hormonal changes ensuing after ovulation [5]. Progesterone is the main factor behind PMS symptoms. The metabolites of progesterone; allopregnanolone and pregnanolone are potent neuroactive steroids. These hormones are positive allosteric modulators of gamma-aminobutyric acid (GABA). Gamma-aminobutyric acid (GABA) is the main inhibitory neurotransmitter in the brain and it is important for regulating stress, anxiety, alertness, and seizure. The progesterone metabolites; allopregnanolone bind with GABA receptor in the brain. This binding changes the configuration of the receptor and decreases its sensitivity to GABA. This lowers serotonin level, which gives rise to symptoms of premenstrual syndrome [5].

Premenstrual syndrome is associated with different socio-demographic factors like age, marital status, and living region [6]. Premenstrual syndrome is also associated with stress due to heavy duties, coffee intake, age at menarche, long menstrual cycles, and being sexually active [7]. Parent’s income and previous history of depression were also associated with premenstrual syndrome [8].

Premenstrual symptoms severely affects the health-related quality of life, increase health care utilization, and decrease work productivity [9, 10]. The decreased productivity at work and performance at school is associated with a lack of concentration, motivation, and poor involvement in collaborative work [11].

Despite the negative impact of PMS on the health-related quality of life, less attention has been given to it. Determining the pooled prevalence of premenstrual syndrome at a country level gives a better figure than discrete primary studies. Therefore, this systematic review and meta-analysis study was aimed to estimate the pooled prevalence of premenstrual syndrome and its associated factors in Ethiopia.

Materials and methods

Search strategy

Systematic review and meta-analysis were done by using Published studies. The articles were searched by electronic databases such as PubMed/Medline, google scholars, HINARI, Science Direct, Cochrane Library, and EMBASE.

The key terms and search strategies used for intensive search were (((associated factors [Title/Abstract] OR risk factors [Title/Abstract]) OR ((prevalence [Title/Abstract] OR magnitude [Title/Abstract]) OR "prevalence"[MeSH Terms])) AND (((premenstrual syndrome [Title/Abstract] OR premenstrual dysphoric disorder [Title/Abstract]) OR premenstrual tension [Title/Abstract]) OR "premenstrual syndrome"[MeSH Terms])) AND (Ethiopia [Title/Abstract] OR "Ethiopia"[MeSH Terms]).

The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were strictly followed in this study [12]. A protocol of the study has been registered by the International Prospective Register of Systematic Reviews(PROSPERO)(ID: CRD42020162498).

Study selection and eligibility criteria

This systematic review and meta-analysis study incorporated all original research articles that reported the prevalence and associated factors of premenstrual syndrome among women of the reproductive age group in different parts of Ethiopia and published until December 25, 2019. All fully available studies written in the English language were included without restriction on their study design. Further tracing of studies was done by direct contact with the corresponding author of the existing article through email.

Before incorporating those studies into our meta-analysis, we reviewed the title and abstract of each study. After selecting relevant studies, the full text was reviewed. Articles with no variables of interest were excluded from our analysis.

Quality assessment

To assess the data quality, a critical appraisal was done by using the Joanna Briggs Institute Meta-Analysis of Statistics Assessment and Review Instrument (JBI-MAStARI) [13]. The tool includes ten questions that address the methodology of the study. The criteria under this question include the representativeness of the sample used, the way of participants recruitment, adequateness of the sample size, the detail description of setting and subjects, use of standard measurement and its reliability, appropriate statistical analysis done with sufficient coverage of identified sample size and identification of subgroups. The components of quality assessment tools were clarified briefly by discussion among researchers. The quality assessment of all articles was done independently by two researchers. After taking the final score of the assessments from the two researchers, any disagreement was resolved by the negotiation of a third researcher. Studies with a score of greater than or equal to 6 out of 10 were considered as high quality and those studies with less than 6 out of 10 were considered as low quality. Those studies with high quality were included in the analysis.

Outcome of interest

In this study, the main outcome of interest was the prevalence of premenstrual syndrome and its associated factors. The variables considered for this systematic review were age, alcohol intake, heavy non-academic duties, sexual activity, hormonal contraceptive use, and menstrual histories such as early menarche and menstrual pattern. The independent variables included in the meta-analysis were age at menarche, menstrual pattern, and hormonal contraceptive use.

Operational definition

In this study, the following operational definitions were used. Age at menarche was divided in to early if ≤ 12 and late if > 12 years [14]. Moreover, the menstrual pattern was divided into a regular; cycle with a regular monthly pattern, and an irregular pattern; cycle with fluctuating monthly pattern as reported by respondents [15].

Data extraction

The two authors (TG and TT) independently extracted all necessary data by using Microsoft excel extraction format. The extracted parameters are the first author’s name, year of publication, study design, sample size, prevalence, and tools used for the diagnosis of premenstrual syndrome. It also includes the number of participants with PMS and those with no PMS in association with the factors; age at menarche, menstrual pattern, and hormonal contraceptives. Then, the extracted data were checked again by the three authors, and disagreement was solved by tracing back to original articles.

Data analysis

Data from Microsoft excel were exported to STATA software version 14 for analysis. The prevalence and standard error of each study were considered to calculate the pooled prevalence of premenstrual syndrome. The pooled prevalence was presented by the forest plot. To reduce the random error on the point estimate of individual studies, subgroup analysis was done based on the study setting (High School and University). The heterogeneity between studies was assessed by the I2 statistical test and p-values less than 0.05 were used to declare it. Due to the presence of significant heterogeneity, the random-effects meta-analysis model was used. The possible source of heterogeneity was checked by meta-regression analysis by considering the publication year, sample size, and quality of the study. Egger’s test was used to assess publication bias, and a p-value of less than 0.05 was used to declare its statistical significance. Odds ratio (OR) with 95% CI was also presented in the forest plot to show the associated factors of PMS.

Results

Study selection

During the search for published primary research articles, we found thirty-three studies. After duplications have been removed, twenty studies were left. These studies were further screened by a review of their title and abstract. Then, eight studies were removed. Among these, six studies have duplication of its content with different citations and publications of the same paper in different journals and the remaining two studies were conducted outside of Ethiopia. Moreover, the outcome of interest was not reported in the three studies and therefore, excluded from this study. Finally, nine studies were selected and included in this systemic review and meta-analysis (Fig 1).

Fig 1

Flow chart showing articles selection strategy for systematic and meta-analysis of prevalence and associated factors of premenstrual syndrome in Ethiopia, 2020.

Study characteristics

All studies included in this analysis were conducted using a cross-sectional study design [7, 8, 16–22]. For eight of these studies, the premenstrual syndrome scoring tool of Diagnostic and Statistical Manual of Mental Disorders, 4th Ed (DMS IV) was used while the American College of Obstetricians and Gynecologists (ACOG) was used for the remaining one study [7]. All the included studies were done from 2002 to 2019 and their sample size ranged from 181 [19] to 667 [17]. The total sample size considered for the pooled prevalence of premenstrual syndrome in the current analysis was 3373. Moreover, all the studies were published articles, and their quality score range from 6 to 9 out of 10 points. Table 1.

Table 1

Characteristics of studies included in the current systematic review and meta-analysis on the prevalence and associated factors of premenstrual syndrome in Ethiopia, 2020.

Author	Year	Study area	Study- design	Sample- size	Prevalence %	Study- setting	Tools
Abeje A. et al	2015	Debre Markos, Amhara region	Cross- sectional	496	81.3	High school	ACOG
Tenkir A. et al	2002	Jima,Oromia region	Cross-sectional	242	27	University	DSM -IV
Alemu M. et al	2017	Debre Berhan, Amhara region	Cross- sectional	667	60.31	University	DSM -IV
Asmare D. et al	2013	Debre Berhan, Amhara region	Cross- sectional	321	41.12	Community	DSM -IV
Desalegn J. et al	2015	Assosa, Benishangul Gumuz region	Cross-sectional	519	58.6	University	DSM -IV
Mossie T. et al	2015	Mekele, Tigrai region	Cross- sectional	181	30.9	High schools	DSM -IV
Muluken TS. et al	2010	Bahir Dar, Amhara region	Cross-sectional	470	72.8	University	DSM -IV
Tollosa & Bekele	2013	Mekele, Tigrai region	Cross- sectional	223	37	University	DSM -IV
Tsegaye D. et al	2018	Wollo, Amhara region	Cross-sectional	254	66.9	University	DSM -IV

Note; ACOG: American College of Obstetrics and Gynecology, DSM-IV: Diagnostic and Statistical Manual of mental disorders IV.

Prevalence of premenstrual syndrome

A wide range of prevalence rates was reported in the nine studies [7, 8, 16–22]. The lowest prevalence of PMS, 27.00% (95% CI: 21.41, 32.59) was reported in a study among Jimma University female students [16]. Whereas, the highest prevalence, 81.30% (95% CI: 77.87, 84.73) was reported in a study done among high school students of Debre Markos town [7]. From these nine studies, the pooled prevalence of premenstrual syndrome in Ethiopia was found to be 53% (95% CI: 40.64, 65.36). High heterogeneity was detected between the studies (I2 = 98.4%, p < 0.001) (Fig 2).

Fig 2

Forest plot on the prevalence of premenstrual syndrome in Ethiopia.

The statistical significance of factors considered to be a possible source of heterogeneity was investigated. Variables such as sample size, year of publication, and quality of the study were investigated using univariate meta-regression models. However, none of these variables was found to be statistically significant Table 2. Moreover, the Egger test showed statistically insignificant publication bias, P = 0.538.

Table 2

Heterogeneity related variables for the prevalence of PMS in the current meta-analysis (based on meta regression).

Variables	Coefficient	SE	P > | t |	(95% confidence interval)
Sample size	0.028	5.896	0.996	(-13.56895, 13.62482)
Year of publication	0.025	5.896	0.999	(-34.46264, 34.51393)
Quality of study	0.027	5.896	0.976	(-1.976467, 2.03019)

Note: SE: Standard Error.

Subgroup analysis

To reduce the heterogeneity between the studies, subgroup analysis was done based on the study settings. Accordingly, the pooled prevalence of PMS among university students is 53.87% (95% CI: 40.97, 67.60). Although the heterogeneity of studies done at university showed improvement (I2 = 97.8%, p < 0.001), significant heterogeneity still exists (Fig 3).

Fig 3

Forest plot on the prevalence of premenstrual syndrome at different study setting in Ethiopia.

Associated factors of premenstrual syndrome

Studies included under this systematic review and meta-analysis reported the factors associated with PMS. A study in high school in Debre Markos town showed that PMS has a statistically significant association with age, participation in heavy non-academic duties, coffee intake, early menarche, long menstrual cycles (> 35 days), and being sexually active [7]. The study at Jimma University also showed that age has a significant association with PMS [16]. Another study reported a previous history of depression and level of income has a significant association with PMS [8]. A study in Assosa Technical and Vocation College reported that there was a significant association between PMS and menstrual irregularity [AOR: 1.36, 95% CI (1.82, 2.25)]. The same study also showed that females not using contraceptive methods for the last six months were 1.92 times more likely to develop PMS as compared to their counterparts [18]. A study among Mekelle high school female students showed that income, cigarette smoking, alcohol, and contraceptive use had no significant association with PMS. However, PMS was significantly associated with duration of menses [AOR = 2.32, 95% CI (1.07, 5.05)] and early menarche [AOR = 3.11 95% CI (1.19, 8.12)] [19].

Pooled odds ratio of associated factors

Age at menarche. Two studies witwere included in this analysis [7, 19]. Age at menarche has a significant association with PMS [7]. Contrariwise, another study found no significant association between age at menarche and PMS [19]. A meta-analysis of the pooled odds ratio shows that women with early menarche were 1.76 times more likely to develop PMS as compared to women with late menarche (OR: 1.76, 95% CI: 0.54, 5.70). However, the association was statistically insignificant. The heterogeneity test showed insignificant heterogeneity between the studies (I2 = 69%, p = 0.073) (Fig 4).

Fig 4

Forest plot on the associated factors of premenstrual syndrome in Ethiopia.

Menstrual pattern

Three studies with a total sample size of 1545 were included to determine the association between menstrual patterns and PMS. Two of these studies show a significant association between menstrual patterns and PMS [18, 20]. However, the remaining study shows a statistically insignificant association between PMS and menstrual patterns [7]. The pooled odds ratio also shows a statistically insignificant association between menstrual pattern and PMS (OR: 3.19, 95% CI: 0.94,10.80) (Fig 4).

Hormonal contraceptive use

Out of the two studies included in this current meta-analysis to determine an association between contraceptive use and PMS [18, 19], one study shows a significant association between hormonal contraceptive use and PMS [18], while the other one shows no significant association between use of oral contraceptive pills and PMS [19]. The pooled odds ratio shows that hormonal contraceptive use had no significant association with PMS (OR: 0.97, 95% CI: 0.23, 4.06) (Fig 4).

Discussion

Regarding the prevalence and associated factors of PMS, this is the first systematic review and meta-analysis study in Ethiopia. Nine primary studies were included in the current systematic review and meta-analysis. This study assessed the prevalence and associated factors of PMS.

The pooled prevalence of PMS is 53% (95% CI: 40.64, 53.36). A subgroup analysis of the current study shows that the pooled prevalence of PMS among university students is 53.87% (95% CI: 40.97, 67.60). This result is in line with the other meta-analysis conducted worldwide [4]. It is also in line with other primary studies [9, 23]. Contrariwise, a higher pooled prevalence of PMS was reported in a meta-analysis study in Iran (70.8%) [24]. However, studies also reported a lower prevalence of PMS as compared to the current study [2, 3, 25–27]. These variations from the current study might be due to differences in sociodemographic factors of the study participants and tools used for PMS screening. It is difficult to determine the true prevalence of PMS in different setup because of self-treatment, differences in availability and access to health services, definition, and diagnostic criteria, and cultural practices [4].

The other aim of the current study is to assess associated factors of premenstrual syndrome. Although PMS is a problem common to women, the clear cause is unknown. It probably has to do with hormonal changes during each menstrual cycle. It gets triggered and associated with different factors.

The pooled odds ratio of the current study shows that PMS has a statistically insignificant association with age at menarche. This result is in line with other studies [2, 9, 28, 29]. Contrariwise to the current study, other studies show that age at menarche has a significant association with PMS [30, 31]. This difference between studies may be due to sociodemographic differences between the study participants.

Among the nine studies included in the current analysis, two studies [20, 22] reported a significant association between menstrual patterns and PMS. This is in line with other studies [2, 26, 29]. But the pooled odds ratio shows an insignificant association between menstrual pattern and PMS (OR: 3.19, 95% CI: 0.94,10.80).

In agreement with another study [32], the pooled odds ratio of the current study shows that hormonal contraceptive use has an insignificant association with PMS. However, a population-based survey in the French found a significant association between PMS and hormonal contraceptive use [2]. This variation in the result may be due to a difference in types of hormones and time duration of hormone use among study participants.

The strength of this study lies in the fact that it is the first meta-analysis and systematic review of the subjects in Ethiopia. However, the study has the following limitations. The analysis was done with few studies, and these studies were limited to the Oromia, Amhara, Benishangul-Gumuz, and Tigrai regions of Ethiopia. Moreover, age at menarche was categorized into two as early (≤ 12) and late (> 12). This is dichotomous category is not sufficient to explain the association between age at menarche and PMS. Also, classifying menstrual pattern as regular and irregular based on women’s report pose a recall bias.

Conclusion

More than half of women under the reproductive age group in Ethiopia are experiencing premenstrual syndrome. The findings of this study provide valuable information for policymakers, health professionals, and other stakeholders to set appropriate implementation strategies to reduce the impact of PMS. Moreover, further large-scale primary studies that focus on a wide range of independent variables are needed.

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Data set on the prevalence of premenstrual syndrome in Ethiopia.

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Data set on associated factors of premenstrual syndrome in Ethiopia.

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22 Jun 2020

PONE-D-20-03722

Prevalence and associated factors of premenstrual syndrome among women of reproductive age group in Ethiopia: systematic review and meta-analysis

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Reviewer #1: Title: Prevalence and associated factors of premenstrual syndrome among women of reproductive age group in Ethiopia: systematic review and meta-analysis

The study by Teshome Gensa Geta et al, on premenstrual syndrome is of importance as it affects women globally who are in their reproductive age. The quality of women’s life during PMS is greatly affected by cluster of emotional, physical, and behavioural symptoms. These symptom expressions can vary between a few days to couple of weeks. As PMS is associated with mood and behavioural symptoms, a study by Kimberly Ann Yonkers et al.,(Lancet. 2008 Apr 5; 371(9619): 1200–1210) clearly described its connection with the brain and further suggested two different methods to treat these symptoms.

In the present study, the authors have claimed to have conducted the first systematic review and meta-analysis study on the prevalence and associated factors of PMS in Ethiopia. The authors have pooled various published original research articles from Ethiopia (until December 25, 2019) on PMS and its associate factors as their dataset. The quality of the dataset had been assessed using the Joanna Briggs Institute Meta-Analysis of Statistics Assessment and Review Instrument (JBI-MAStARI) while data analysis had been performed using the STATA software version 14.

From the 33 original research articles, using various criteria the authors have chosen to use the data only from 9 studies which has the total sample size of 3373 and considered for further analysis. The authors show that the pooled prevalence of PMS in Ethiopia was 53%(95% CI: 4064, 65.36). Further, high heterogeneity had also been detected in their study samples (I2 = 98.4%, p < 0.001). The authors have taken various factors into consideration like sample size, year of publication and quality of study to investigate the possible source of heterogeneity using statistical methods, however, the results were found to be insignificant. Eager test too showed insignificant P-value of P = 0538.

In order to reduce the heterogeneity, the authors have also performed the subgroup analysis based on study settings and found that the pooled prevalence of PMS among university students was 53.87% (95% CI: 40.97, 67.60). The result shows that though significant heterogeneity had been observed, there was some improvement of heterogeneity at the university level.

The authors have also studied various associated factors of PMS and show that, age, irregular menses, duration of menses, menstrual pattern has a statistically significant association with PMS among some of the high school and university students. Further age at menarche also had a significant association with PMS. In contrast a study done at Mekelle high school female students showed that income, cigarette smoking, alcohol, and contraceptive use had no significant association with PMS.

Based on the analysis and the results, the authors conclude that pooled prevalence of PMS in Ethiopia was 53% indicating that half of the Ethiopian women were suffered from PMS in their reproductive years. This number may vary across countries due to various factors such as socio-demographic, individual life-style, marital status etc. The pooled odds ratio showed that age at menarche, menstrual pattern and hormonal contraceptive use had statistically insignificant association with PMS.

The limitation of this study was restricted only with high school and university students who live in Oromia, Amhara, Benishangul-Gumuz and Tigrai region of Ethiopia.

The authors have carried out a significant work in understanding the PMS in different regions of Ethiopia among high school and university students. I hope the authors may work with the larger data in the future which could also include working women, married/unmarried in their dataset. Further, as PMS symptoms are mostly associated with mood and behaviour, I would also suggest the authors to discuss and co-relate their findings with the receptors expressed in the brain, such as serotonin and its associated receptors.

PS: I have a small concern, the Figure 1 ‘Fig 1: flow chart showing articles selection strategy‘ have a very high similarity to the Figure 1 from the previously published article by Ashraf Direkvand-Moghadam et al., J Clin Diagn Res. 2014 Feb; 8(2): 106–109. I have provided the link to this article below:

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3972521/

Kindly make changes in your Figure 1 before it’s been accepted for publication. Further, I would also suggest the author to proof read the manuscript with a native English speaker to improve standard of English in the manuscript.

This manuscript may be accepted for publication in the current form after the suggested corrections as their objective of the had been addressed.

My best wishes to all the authors.

Thank you.

Reviewer #2: This analysis – designed to estimate the pooled prevalence of Premenstrual Syndrome, PMS, and its associated factors in Ethiopia – followed a reasonable strategy to review published studies. It concludes that that the majority of reproductive aged high school and college aged women do experience PMS. The paper needs to be strengthened to render that conclusion credible.

Essential ms changes that should be made before consideration for publication include

1. Offer the reader a clear definition of what constitutes PMS since no disease is associated per the definition offered. Well-known hormonal shifts have been clearly defined in the literature.

a. The current definition of PMS is too vague and could apply to any fertile aged prescient woman who undergoes the well characterized sequential peak in progesterone approximately 7 days after ovulation and its subsequent decline to undetectable levels by menses onset. Since estrogen levels also plunge as P levels do, the assertion that P declines are responsible for PMS should be explained or omitted.

b. How is the “syndrome” diagnosed? Self-administered questionnaire then scored using standard procedures?

i. Can the authors provide a supplement for interested readers to review?

c. Does a health care worker make an assessment after interview?

d. Does a woman have to complain of the problem for it to be identified as PMS?

e. Who makes the judgment that this is a “syndrome” rather than a normal variation in energy and mood cycles?

2. An English language editor is essential because the word usage is frequently erroneous. For example, these underlined words do not make sense and the reader is left guessing what the authors probably mean:

a. Line 57 each of the three precede menstrual cycles

b. Line 61 The… meta-analysis did worldwide

c. Line 69-70 with joining in heavy duties… initial menarche

d. Line 71 being sexually active among students

e. Line 73-4 may outcome

f. Line 78 has given on it.

g. Line 103 .for studies that were not shown the outcome of

h. Line 114 after a brief discussion on the tool.

i. Line 117 those studies with less than 5 scores

j. Line 195 A study at high school students

k. Line 212 In contrary to this study…

3. Outcome of Interest

a. Independent variables chosen should be improved

i. Age at menarche was simply divided into two groups: those 12 or younger and those older. This seems too gross a division to hope to find an effect of age on PMS if avg age of menarche in Ethiopia mirrors the US at about 12 yrs. It would be more meaningful to divide groups into at least 3 or better yet 5 age groups: very early, early, average, mildly late, and very late. If you did, it would be interesting to learn about the relationship between the syndrome and the age

ii. Menstrual pattern as regular or irregular should be clearly explained: did women keep records of their menses that scholars extracted data from? Recall has been shown to be not useful in multiple studies that showed strong relationships between menstrual pattern and hormonal outcomes.

4. Results

a. Figures 2, 3 and 4 each need a legend to explain the scale on the x axis. For example, on Figure 4, I wonder how a prevalence could be less than zero. Or why -84.7 is even labelled?

b. The study characteristics Tools should be explained so that readers can understand how they measure their “findings.” (Please see point 1a above).

c. The prevalence outcome beginning on line 170 is clearly stated. Once the reader knows how the measures were obtained, the prevalence [in more than half the women] can be better understood to evaluate the importance of the findings.

d. Beginning line 227 It would be interesting to learn what kind of contraceptives were used in the study that did and the study that did not find a relationship to PMS. Some drugs flatten out the hormonal environment; others elevate and depress hormonal levels in sequence.

5. The strength of the study statement is good. As well as the limitations. Except for the misuse of English in line 273: were suffered from PMS.

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Reviewer #1: No

Reviewer #2: No

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1 Aug 2020

Response to comments from editor and reviewer

Manuscript ID number: PONE-D-20-03722

Prevalence and associated factors of premenstrual syndrome among women of reproductive age group in Ethiopia: systematic review and meta-analysis

We would like to express our heartfelt gratitude to editor and reviewers for constructive comments and guidance which are extremely helpful to improve this manuscript. Here are point-by-point responses for the comment raised. We had thoroughly revised the manuscript and provided the amendments that have been made to the manuscript text.

Response to Editor comments

1. The manuscript thoroughly edited based on PLOS ONE's manuscript writing format.

2. The data from which result and conclusion drawn was attached as one of supporting information.

3. The captions for Supporting Information files were written at the end of manuscript

Response to Reviewer 1 Comments

1. Similarity of Figure 1 on flow chart showing articles selection strategy with previous published work was resolved.

2. English language edition was done by language editor.

John Odjenimah, email: ighoyiwi25@gmail.com

Response to Reviewer 2 Comments

1. A. The definition of premenstrual syndrome was clarified.

B – E. Comment on this sub – section concerning diagnosis of PMS is very important but the scope of the current study not extends up to the level of evaluating diagnostic tools. As describe in the manuscript, all primary studies included in the current study were cross sectional studies. Those studies done by using two standard tools to diagnosis PMS such as American College of Obstetrics and Gynecology (ACOG) and Diagnostic and Statistical Manual of mental disorders IV (DSM-IV).

For clarification on diagnosis of PMS by using ACOG; diagnostic criteria were described in paragraph two in introduction section.

2. All the indicated (subsection A -K ) and other section of manuscript were edited for English language by language editor.

3. Independent variables

I. Age at menarche was divided into two groups: those 12 or younger and those older. This is classification done by primary studies. Indeed, it has limitation to describe association with PMS. Thus, we described this as limitation of study on manuscript.

II. Dividing menstrual pattern as regular or irregular was based on women’s report which is not based on record during each menses. All the study available on this title were cross sectional. So, we indicated recall bias as one of limitation of study.

4. A. The figures were edited accordingly and possible amendments were done. Figure 2 is forest plot that shows prevalence of PMS in Ethiopia. The labeled 84.7 is maximum confidence interval level for prevalence of PMS. Figure 3 also show prevalence of PMS in different settings. In both forest plots, dotted line is pooled prevalence and forests shows how weighted prevalence from each study spread around pooled prevalence.

Figure 4 shows odds ratio of associated factors. It may be mis-communication, there is no prevalence indicated as less than zero in manuscript.

B. Diagnostic criteria of PMS was described in paragraph two of introduction section.

C. This comment was applied in the different sections of manuscript

5. Language edition to whole part of manuscript was done

Submitted filename: Response to Reviewers.docx

Click here for additional data file.

2 Sep 2020

PONE-D-20-03722R1

Prevalence and associated factors of premenstrual syndrome among women of reproductive age group in Ethiopia: systematic review and meta-analysis

PLOS ONE

Dear Dr. Geta,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

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We look forward to receiving your revised manuscript.

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Nülüfer Erbil, Ph.D, Prof.

Academic Editor

PLOS ONE

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

Reviewer #2: (No Response)

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2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

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3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

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4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

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5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

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6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: My best wishes to the authors and I wish the authors may carry out the study with a larger sample size across all over Ethiopia in the future.

Reviewer #2: The authors did a fine job of revising the manuscript and I have only a few remaining comments. I will not need to review the paper again and am fine with publishing it once these are considered.

1. 2 typos need to be fixed: first on line 60: ‘relieved’ is the correct spelling; not relived; then on line 64 add an “s” to pluralize the word “cycle”

2. The quality assessment paragraph beginning with line 115 is nice but there seems to be no mention of the relative quality assessments of the 9 studies that are analyzed. The careful reader will wonder which of the 9 were high-quality papers and whether these produced a more consistent outcome than putting them all in one basket. I assumed there was no quality restriction for inclusion. But I am left uncertain. The results did not provide this information. Or I missed it?

3. Line 295, I suggest “suffering” is not an appropriate term. We really cannot tell whether cyclic variation in mood, and energy which alters ones “normal activity” causes pain and suffering. In fact, the energy swing itself might be part of the human condition of what constitutes normal. Women are not robots and cyclic variation in energy and mood sufficient to alter how one engages in the work and other activities is a rational response to hormonal and metabolic change. I would suggest using the word “experiencing” rather than “suffering”. Considering that about half of women experience these swings might suggest that medicalizing such experience is not such a wise idea.

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Reviewer #1: No

Reviewer #2: Yes: Winnifred Cutler

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

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Submitted filename: decision.docx

Click here for additional data file.

14 Sep 2020

Response to reviewer 1 comment

Constructive comment for future progress in the area was well accepted

Response to Reviewer 2 comments

1. Two words with type error have been corrected

Line 60: relived is replaced by relieved

Line 64: cycle is replaced by cycles’

2. Clarification on quality assessment and selection of articles has been done by adding the following sentence.

Line 127 in quality assessment under method’s sections: Those studies with high quality (quality score of 6 and more) were included in the analysis

Line 178 in study characteristics under result section: All the studies were published articles and their quality score range from 6 to 9 out of 10 points.

3. Line 295, comment on the word usage was considered and the appropriate term was replaced

Line 296: suffering is replaced by experiencing

Submitted filename: response to reviewer.docx

Click here for additional data file.

20 Oct 2020

Prevalence and associated factors of premenstrual syndrome among women of reproductive age group in Ethiopia: systematic review and meta-analysis

PONE-D-20-03722R2

Dear Dr. Geta,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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Kind regards,

Nülüfer Erbil, Ph.D, Prof.

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

26 Oct 2020

PONE-D-20-03722R2

Prevalence and associated factors of premenstrual syndrome among women of the reproductive age group in Ethiopia: systematic review and meta-analysis

Dear Dr. Geta:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

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Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

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on behalf of

Dr. Nülüfer Erbil

Academic Editor

PLOS ONE