Sociodemographic, reproductive, and psychiatric factors associated with menstrual distress in Indonesian women: findings from an online survey using the MEDI-Q

Our study demonstrated a statistically significant negative correlation (p < 0.01) between age and MEDI-Q Total score, MS score, MSD score, and MESI, indicating that increasing age is associated with lower MEDI-Q scores across all assessed domains. Consistent with previous research reporting that women aged 15–30 years had significantly higher mean menstrual distress score compared to those aged ≥ 30 years old [ 26 ]. Another study demonstrated that the risk of dysmenorrhea was 0.97 times lower as age increased [ 27 ]. Older women tend to report milder menstrual symptoms, potentially due to greater life experience and development of effective strategies to manage cyclical menstrual discomfort, including lifestyle modifications, social support, and self-care routines. Additionally, hormonal changes associated with aging and major life transitions can modulate the expression and reporting of symptoms at different ages. A reduction in the prevalence of premenstrual symptoms among older women is also partly explained by the decreased frequency of ovulatory cycles as women grow older [ 27 – 29 ]. Progesterone, which fluctuates significantly during the menstrual cycle, plays a dual role in pain modulation. It has been shown to exert a protective effect against pain by interacting with GABAᴬ. Conversely, PGs lead to increased uterine tone and high-amplitude contractions, which are perceived as painful stimuli. As women age and experience reproductive transitions, the stability of progesterone levels and the potential decrease in PGs sensitivity may contribute to the observed reduction in symptom severity. Consequently, older women may report milder symptoms not only due to psychosocial adaptation but also due to these underlying physiological shifts that dampen the hyper-contractility and neuro-sensitization associated with younger reproductive ages [ 30 – 32 ].

In the present study, women with reproductive disorders such as uterine fibroids (UFs), endometriosis, and polycystic ovary syndrome (PCOS), exhibit higher MEDI-Q Total and MS scores. This finding may be explained by the fact that women with reproductive disorders experience greater baseline physiological distress and more severe menstrual symptoms compared to women without such conditions [ 20 ]. A study by Vannuccini [ 21 ] revealed that individuals with UFs experienced a significantly higher prevalence of HMB and longer menstrual duration compared to controls. Significantly elevated scores on the Total MEDI-Q, MSD, and MESI were found in the UFs group, further supporting the association between reproductive disorders like UFs with elevated perceived stress and the exacerbation of menstrual symptoms. Another study by Evans [ 44 ] revealed that individuals with endometriosis experienced a significantly higher Numeric Rating Scale (NRS) score, consistent with our findings and further supporting the hypothesis that women with endometriosis experience more severe menstrual symptoms [ 44 , 45 ]. A cross-sectional study by Almahareeq [ 46 ] demonstrated that PCOS patients had significantly greater PMS severity across physical, behavioral, and psychological domains. In line with study by Kumari [ 47 ], which reported that the frequency of dysmenorrhea among people with PCOS was higher than in healthy subjects. These similar findings may be explained by the fact that women with reproductive disorders experience greater baseline physiological distress and more severe menstrual symptoms compared to women without such conditions [ 48 , 49 ]. In the present study, women with psychiatric disorders—including depression, bipolar disorder, and anxiety—demonstrated significantly higher MEDI-Q Total, MS, and MSD scores. Accurate clinical assessment of premenstrual symptoms in these populations is crucial. As highlighted in a recent comprehensive review on the clinical evaluation of premenstrual disorders, retrospective self-reporting of symptoms is highly unreliable and frequently leads to the overdiagnosis of Premenstrual Dysphoric Disorder (PMDD). Notably, clinical data suggests that a significant proportion of women seeking treatment for severe premenstrual mood symptoms suffer from the Premenstrual Exacerbation (PME) of an underlying psychiatric condition. To avoid misdiagnosis, the authors strongly advocate for the implementation of prospective daily symptom rating scales across at least two consecutive menstrual cycles, which is essential to definitively distinguish true PMDD from PME [ 50 ]. This aligns with recent contributions exploring the broader relationship between menstrual-cycle fluctuations and psychiatric illness, which emphasize that women with pre-existing mental health conditions are particularly vulnerable to PME due to a heightened sensitivity to normal neuroactive steroid shifts. In a 2024 review under Sequenced Treatment Alternatives to Relieve Depression (STAR*D), it was revealed that 64% women with major depressive disorder (MDD) experience premenstrual worsening of mood and physical symptoms, which explains the complex interplay between the menstrual cycle and mood disorders [ 51 ]. A 2021 review on women with bipolar disorder found that they experience a more complex illness course, with increased psychiatric comorbidities and greater symptom severity during the menstrual cycle [ 52 ]. Another study by Nilni revealed that women with anxiety-related disorders consistently report worsening of menstrual symptoms in the luteal phase, likely driven by a premenstrual sharp decline of estradiol, progesterone, and progesterone metabolites in the late luteal phase, leading to diminished GABAergic tone and heightened neuronal excitability. Concomitant increases in adrenal steroids such as DHEA, which facilitate NMDA receptor activity and antagonize GABAᴬ function, further tip the balance toward excitation and exacerbate anxiety symptoms [ 53 ]. These study findings may be attributable to the additional psychological stress imposed by these psychiatric conditions, which can heighten the perception and severity of somatic symptoms, including those related to menstruation, compared to women without such disorders [ 11 , 51 ]. The results obtained in this study are based on a relatively small sample size of subjects with a history of psychiatric disorders, which may introduce potential bias. Further studies with larger sample sizes within specific psychiatric disorder subgroups are necessary to confirm the relationship between psychiatric history and MEDI-Q scores. It is important to acknowledge that reproductive and psychiatric disorders are inherently linked to higher levels of pain and emotional distress, acting as major unadjusted confounding variables in our analysis. However, rather than excluding these populations, they were deliberately retained to capture a pragmatic, real-world epidemiological profile. In the general Indonesian population, many women remain undiagnosed or continue to participate in daily work and educational activities despite the heavy burden of these underlying conditions. Excluding them would have artificially restricted our sample and significantly reduced the external validity of our findings for public health applications. Therefore, while our results represent aggregate effects, they successfully demonstrate the MEDI-Q's high utility as a sensitive 'first-line' community screening tool. By capturing this elevated baseline distress, the MEDI-Q can effectively identify vulnerable women who require further medical evaluation, even before formal diagnoses are established. Future research utilizing multivariable adjustments is still warranted to precisely isolate the independent effects of these clinical conditions from other sociodemographic factors.

Table 1 presents the sociodemographic and clinical characteristics of the study participants. A total of 944 of women responded to the online survey. Following an initial screening, 14 respondents were excluded from the analysis either due to submitting incomplete data or meeting the exclusion criteria. Consequently, a final sample of 930 women were included, with a mean age of 31.57 ± 6.89 years and a mean menarche age of 13.07 ± 1.668 years. The majority of participants were employed (77.6%) and had attained at least a vocational level of education (74.3%). Regarding menstrual health, most participants reported having a regular menstrual cycle (81.4%) and a normal menstrual duration (85.5%). In terms of contraceptive use, 64.5% had no history of contraceptive usage, while among those who did, hormonal contraception were the most commonly used method (61.8%). Additionally, a small proportion of participants had a history of reproductive diseases (7.1%) or psychiatric disorders (3.4%). Table 1 General Characteristics of The Participants Characteristics n  = 930 Age 31.57 ± 6.89 Menarche 13.07 ± 1.668 Educational Degree  Vocational above 691 (74.3%)  Highschool graduate or lower 239 (25.7%) Occupational Status  Working 722 (77.6%)  Unemployed 208 (22.4%) Menstrual Cycle Interval   35 days 78 (8.4%) Menstrual Cycle Duration   7 days 121 (13%) Contraceptive usage  No 600 (64.5%)  Yes 330 (35.5%) Type of Contraception  Hormonal 204 (61.8%)  Non-Hormonal 126 (38.2%) History of Reproductive Diseases  Yes 66 (7.1%)  No 864 (92.9%) History of Psychiatry Disease  Yes 32 (3.4%)  No 898 (96.6%)  MEDI-Q Total Scores (0–125) 8.45 ± 11.086  MS score 4.35 ± 4.320  MSD score (0–5) 1.35 ± 0.943  MESI score (0–1) 0.4735 ± 0.388 Data are presented by n (%) and mean ± standard deviation MEDI-Q Menstrual distress questionnaire, MS menstrual symptoms, MSD menstrual symptoms distress, MESI menstrual specificity index General Characteristics of The Participants Data are presented by n (%) and mean ± standard deviation MEDI-Q Menstrual distress questionnaire, MS menstrual symptoms, MSD menstrual symptoms distress, MESI menstrual specificity index For menstrual distress assessment, the mean MEDI-Q total score was 8.45 ± 11.086, while the mean scores for MS, MSD, and MESI were 4.35 ± 4.320, 1.35 ± 0.943, and 0.4735 ± 0.388, respectively. These values provide insight into the severity and specificity of menstrual symptoms experienced by the participants. Average distress scores computed for each item are presented in Table  2 , showing that lower abdominal pain, sadness, feeling of being impure, muscle/osteoarticular pain, and emotional lability obtained the highest scores. Table 2 Average Distress Score for Each MEDI-Q Items Item Number Item Description Mean SD Item 1 Lower abdominal pain 0.954 1.257 Item 2 Urinary pain 0.071 0.343 Item 3 Pain at defecation 0.147 0.609 Item 4 Muscle/osteoarticular pain 0.600 1.067 Item 5 Breast tenderness/widespread swelling sensation 0.554 1.029 Item 6 Nausea 0.189 0.636 Item 7 Headache 0.393 0.910 Item 8 Pain during sexual intercourse 0.207 0.673 Item 9 Digestive problems 0.124 0.512 Item 10 Diarrhea 0.078 0.448 Item 11 Constipation 0.423 1.058 Item 12 Feeling uncomfortable about vagina blood loss 0.281 0.856 Item 13 Feeling of being impure 0.647 1.198 Item 14 Sadness 0.791 1.329 Item 15 Emotional lability 0.600 1.148 Item 16 Irritability/anger 0.116 0.528 Item 17 Impulsiveness 0.192 0.676 Item 18 Anxiety 0.458 0.996 Item 19 Increased appetite 0.260 0.796 Item 20 Decreased appetite 0.121 0.542 Item 21 Insomnia 0.222 0.696 Item 22 Hypersomnia 0.576 1.117 Item 23 Fatigue 0.157 0.679 Item 24 Decreased sexual drive 0.205 0.676 Item 25 Concentration impairment 0.051 0.409 SD standard deviation Average Distress Score for Each MEDI-Q Items SD standard deviation Our study results demonstrated a statistically significant negative correlation between age and all assessed MEDI-Q scores. Specifically, age was inversely correlated with the MEDI-Q Total score, MS score, MSD score, and MESI score (r: –0.345, –0.383, –0.372, and –0.157, respectively). These findings indicate that increasing age is associated with lower MEDI-Q scores across all domains assessed. All correlations remained significant at the 0.01 level (2-tailed) (Table  3 ). Table 3 Correlation MEDI-Q Scores with Age MEDI-Q Total MS MSD MESI Age Pearson Correlation -.345 -.383 -.372 -.157 Sig.(2-tailed)  <.001**  <.001**  <.001**  <.001** * Significant at the 0.05 level ** Significant at the 0.01 level Correlation MEDI-Q Scores with Age * Significant at the 0.05 level ** Significant at the 0.01 level As shown in the scatter plots (Fig.  1 ), the R 2  values for the relationships between age and the MEDI-Q Total, MS, MSD, and MESI scores were 0.019, 0.147, 0.0138, and 0.025, respectively. This indicates that age accounts for approximately 1.9%, 14.7%, 1.4%, and 2.5% of the variance in these specific symptom domains. Fig. 1 Relationship Between MEDI-Q Scores and Age: Scatter Plot Visualization Relationship Between MEDI-Q Scores and Age: Scatter Plot Visualization Each scatter plot illustrates the linear relationship between age and four MEDI-Q score domains: (A) MEDIQ Total Score; (B) MS Score; (C) MSD Score, and (D) MESI. Regression lines and corresponding  R 2  values are included for each plot to show the strength of association. All data points represent individual participants. Lower R 2 values indicate a weak linear association in these samples. MEDIQ Total = Menstrual Distress Questionnaire Total; MS = Menstrual Symptoms; MSD = Menstrual Symptoms Distress; MESI = Menstrual Specificity Index. The analysis revealed that educational background significantly influenced MS scores, with participants holding vocational qualifications or higher exhibiting higher scores (Z: −2.230, p: 0.026) (Table  4 ), while for the MEDI-Q Total Score, MSD, and MESI, the difference was not statistically significant (p > 0.05). This suggests that while MS scores are associated with educational background, other measures remain unaffected by this variable. Table 4 Educational Background and MEDI-Q Scores MEDI-Q Scoring Last Educational Background N Median (IQR) U Z p MEDI-Q Total Score Vocational and Above 691 4.00 (11.00) 77,436.0 −1.443 0.149 Highschool Graduate and Lower 239 3.00 (10.00) MS Vocational and Above 691 3.00 (6.00) 74,648.5 −2.230 0.026* Highschool Graduate and Lower 239 2.00 (5.00) MSD Vocational and Above 691 1.25 (1.00) 81,714.5 -.243 0.808 Highschool Graduate and Lower 239 1.33 (1.00) MESI Vocational and Above 691 0.50 (0.84) 80,391.0 -.622 0.534 Highschool Graduate and Lower 239 0.50 (0.84) * Significant at the 0.05 level P Value was obtained using the Mann–Whitney U test MEDI-Q Menstrual distress questionnaire, MS menstrual symptoms, MSD menstrual symptoms distress, MESI menstrual specificity index Educational Background and MEDI-Q Scores * Significant at the 0.05 level P Value was obtained using the Mann–Whitney U test MEDI-Q Menstrual distress questionnaire, MS menstrual symptoms, MSD menstrual symptoms distress, MESI menstrual specificity index The analysis demonstrated a significant association between occupational status and both the MEDI-Q Total Score and MS, with higher scores observed among participants who were employed (Z: –2.245 and –2.720, respectively) (Table  5 ), suggesting an association of MEDI-Q scores with occupational status. The MSD and MESI scores were also higher in the employed, however, the difference was not statistically significant ( p  > 0.05). Table 5 Occupational Status and MEDI-Q Scores MEDI-Q Scoring Occupational Status N Median (IQR) U Z p MEDI-Q Total Score Employed 722 4.00 (11.00) 67,465.0 −2.245 0.025* Unemployed 208 3.00 (8.5) MS Employed 722 3.00 (6.00) 65,867.5 −2.720 0.007** Unemployed 208 2.00 (4.75) MSD Employed 722 1.25 (1.00) 71,357.0 −1.108 0.268 Unemployed 208 1.20 (1.75) MESI Employed 722 0.50 (0.83) 71,450.0 −1.087 0.277 Unemployed 208 0.42 (0.85) * Significant at the 0.05 level ** Significant at the 0.01 level P -value was obtained using the Mann–Whitney U test MEDI-Q Menstrual distress questionnaire, MS menstrual symptoms, MSD menstrual symptoms distress, MESI menstrual specificity index Occupational Status and MEDI-Q Scores * Significant at the 0.05 level ** Significant at the 0.01 level P -value was obtained using the Mann–Whitney U test MEDI-Q Menstrual distress questionnaire, MS menstrual symptoms, MSD menstrual symptoms distress, MESI menstrual specificity index In terms of association with history of contraceptives, all scores except MESI were significantly higher among participants with no history of contraceptives use (Z: –8.156, –8.088, and –6.265, respectively) (Table  6 ), suggesting an association of MEDI-Q scores with history of contraceptive use. The MESI score was higher in the group with no history of contraceptive use (Z: –1.889, p > 0.05); however, the difference was not statistically significant. Table 6 History of Contraceptive and MEDI-Q Scores MEDI-Q Scoring History of Contraceptive N Median (IQR) U Z p MEDI-Q Total Score Yes 330 2.00 (5.25) 67,198.5 −8.156  <.001** No 600 6.00 (13.00) MS Yes 330 2.00 (4.00) 67,519 −8.088  <.001** No 600 4.00 (7.00) MSD Yes 330 1.00 (1.67) 74,766.5 −6.265  <.001** No 600 1.39 (1.00) MESI Yes 330 0.40 (1.00) 91,737.5 −1.889 0.059 No 600 0.50 (0.71) ** Significant at the 0.01 level P Value was obtained using the Mann–Whitney U test MEDI-Q Menstrual distress questionnaire, MS menstrual symptoms, MSD menstrual symptoms distress, MESI menstrual specificity index History of Contraceptive and MEDI-Q Scores ** Significant at the 0.01 level P Value was obtained using the Mann–Whitney U test MEDI-Q Menstrual distress questionnaire, MS menstrual symptoms, MSD menstrual symptoms distress, MESI menstrual specificity index In terms of contraceptive type, whether hormonal or non-hormonal, there were no statistically significant differences in MEDI-Q Total Score, MS, MSD, and MESI (p > 0.05) (Table  7 ). This suggests that the type of contraceptive used did not influence MEDI-Q scores. Table 7 Type of Contraceptive and MEDI-Q Scores MEDI-Q Scoring History of Contraceptive N Median (IQR) U Z p MEDI-Q Total Score Hormonal 204 2.00 (5.00) 11,813.0 −1.251 0.211 Non hormonal 126 3.00 (7.00) MS Hormonal 204 2.00 (4.00) 11,648.0 −1.454 0.146 Non hormonal 126 2.00 (5.00) MSD Hormonal 204 1.00 (1.50) 12,465.5 -.472 0.637 Non hormonal 126 1.00 (1.70) MESI Hormonal 204 0.40 (1.00) 12,735.5 -.144 0.885 Non hormonal 126 0.34 (0.88) P Value was obtained using the Mann–Whitney U test MEDI-Q Menstrual distress questionnaire, MS menstrual symptoms, MSD menstrual symptoms distress, MESI menstrual specificity index Type of Contraceptive and MEDI-Q Scores P Value was obtained using the Mann–Whitney U test MEDI-Q Menstrual distress questionnaire, MS menstrual symptoms, MSD menstrual symptoms distress, MESI menstrual specificity index The analysis demonstrated that the presence of reproductive diseases had a significant impact on the MEDI-Q Total Score and MS, with participants diagnosed with reproductive diseases exhibiting higher scores (Z = −2.296 and Z = −2.308, respectively) (Table  8 ). However, no statistically significant differences were observed for MSD and MESI ( p  > 0.05). Table 8 Reproductive Disorders and MEDI-Q Scores MEDI-Q Scoring History of Reproductive Disease N Median (IQR) U Z p MEDI-Q Total Score Yes 66 7.00 (11.00) 23,706.5 −2.296 0.022* No 864 4.00 (11.00) MS Yes 66 4.50 (6.25) 23,691.5 −2.308 0.021* No 864 3.00 (6.00) MSD Yes 66 1.53 (1.00) 25,065.0 −1.661 0.097 No 864 1.22 (1.00) MESI Yes 66 0.48 (0.65) 27,599.5 -.442 0.658 No 864 0.50 (0.85) * Significant at the 0.05 level P Value was obtained using the Mann–Whitney U test MEDI-Q Menstrual distress questionnaire, MS menstrual symptoms, MSD menstrual symptoms distress, MESI menstrual specificity index Reproductive Disorders and MEDI-Q Scores * Significant at the 0.05 level P Value was obtained using the Mann–Whitney U test MEDI-Q Menstrual distress questionnaire, MS menstrual symptoms, MSD menstrual symptoms distress, MESI menstrual specificity index The analysis demonstrated a significant association between the presence of psychiatric diseases on MEDI-Q Total Score, MS, and MSD, with higher scores observed among participants diagnosed with psychiatric diseases (Z: –4.969, –4.545, and –5.007, respectively) (Table  9 ), suggesting an association of MEDI-Q scores with a history of psychiatric diseases. The MESI score was also higher in the group with the presence of psychiatric diseases; however, the difference was not statistically significant (p > 0.05). Nevertheless, the results obtained in this study are based on a relatively small sample size of subjects with a psychiatric history. Table 9 Psychiatric Disorders and MEDI-Q Scores MEDI-Q Scoring History of Psychiatric Disease N Median (IQR) U Z p MEDI-Q Total Score Yes 32 18.5 (24.25) 6986.0 −4.969  <.001** No 898 4.00 (10.00) MS Yes 32 7.50 (8.25) 7628.5 −4.545  <.001** No 898 3.00(6.00) MSD Yes 32 2.17 (1.07) 6990.0 −5.007  <.001** No 898 1.2 (1.0) MESI Yes 32 0.69 (0.62) 11,640.5 −1.862 0.063 No 898 0.50 (0.83) ** Significant at the 0.01 level P Value was obtained using the Mann–Whitney U test MEDI-Q Menstrual distress questionnaire, MS menstrual symptoms, MSD menstrual symptoms distress, MESI menstrual specificity index Psychiatric Disorders and MEDI-Q Scores ** Significant at the 0.01 level P Value was obtained using the Mann–Whitney U test MEDI-Q Menstrual distress questionnaire, MS menstrual symptoms, MSD menstrual symptoms distress, MESI menstrual specificity index

This study was conducted using a cross-sectional, observational, analytic design to evaluate factors associated with menstrual distress among reproductive-age women based on the MEDI-Q online survey, from April to September 2025. To accommodate the vast geographical landscape of Indonesia and reach a broad, diverse population of reproductive-age women; a web-based survey design was employed. This self-administered, online approach was specifically chosen to facilitate large-scale data collection while ensuring the utmost privacy and comfort of participants when disclosing sensitive information regarding their menstrual, reproductive, and psychiatric health. The inclusion criteria for this study were female gender, ages ranging from 15 to 49 years, native Indonesian Speakers, and having experienced at least three menstrual cycles in the past 12 months. The exclusion criteria were females who were unable to complete the questionnaire due to any condition, females who were not proficient in the Indonesian language or illiterate in the Indonesian language, and individuals who are unwilling to sign the informed consent form or to participate in the study. A sample size calculation using a statistical power of 80%, an effect size of 0.2, and a significance level (alpha) of 0.05, a minimum of 866 research subjects would be required to adequately power this study. The recruitment process utilized the Indonesian version of the MEDI-Q questionnaire, which was implemented via Google Forms via consecutive sampling. The Indonesian version of the MEDI-Q questionnaire has been demonstrated to be a reliable instrument. Test–retest reliability was assessed using the Intraclass Correlation Coefficient (ICC), which yielded a value of 0.892. Additionally, internal consistency, as measured by Cronbach's alpha, was 0.972. These results indicate that the Indonesian MEDI-Q exhibits excellent reliability for use in both clinical and research settings [ 6 ]. History of reproductive and psychiatric disease was based on self-reported lifetime history of a clinical diagnosis made by a healthcare professional. Missing data were excluded, and duplicate data underwent a data cleaning process to ensure data quality and accuracy. The survey link was distributed through various online platforms—specifically Instagram, WhatsApp, and Twitter—to access the target population. MEDI-Q divided into four main sub-items [ 11 ]: (A) Frequency score – to measure how often a symptom occurs during menstruation Scale ranges from 0 (never occurs), 1 (occurs in less than half of menstruations), and 2 (occurs in more than half of menstruations). (B) Menstrual distress score – to evaluate the level of distress caused by the symptom during menstruation Scale ranges from 0 (no distress), 1 (slight distress), 2 (moderate distress), and 3 (severe distress). (C) Premenstrual phase distress score – to evaluate the level of distress caused by the symptom during premenstrual phase Scale ranges from 0 (no distress), 1 (slight distress), 2 (moderate distress), and 3 (severe distress). (D) Intermenstrual phase distress score–to evaluate the level of distress caused by the symptom during the days between the end of menstruation and the premenstrual phase. Scale ranges from 0 (no distress), 1 (slight distress), 2 (moderate distress), and 3 (severe distress). Frequency score – to measure how often a symptom occurs during menstruation Scale ranges from 0 (never occurs), 1 (occurs in less than half of menstruations), and 2 (occurs in more than half of menstruations). Menstrual distress score – to evaluate the level of distress caused by the symptom during menstruation Scale ranges from 0 (no distress), 1 (slight distress), 2 (moderate distress), and 3 (severe distress). Premenstrual phase distress score – to evaluate the level of distress caused by the symptom during premenstrual phase Scale ranges from 0 (no distress), 1 (slight distress), 2 (moderate distress), and 3 (severe distress). Intermenstrual phase distress score–to evaluate the level of distress caused by the symptom during the days between the end of menstruation and the premenstrual phase. Scale ranges from 0 (no distress), 1 (slight distress), 2 (moderate distress), and 3 (severe distress). MEDI-Q score outcomes [ 11 ]: (A) MEDI-Q Total Score is obtained from the sum of all the distress scores calculated for each item. The minimum score obtainable is 0 and the maximum score is 125. (B) Menstrual Symptoms (MS) Score reflects the total number of symptoms that generate distress more during menstruation than in intermenstrual days. It is obtained from the total number of symptoms that generate distress more during menstruation than in intermenstrual days. It is represented by the number of items for which the score obtained in sub-item (B) is greater than that in sub-item (D). (C) Menstrual Symptoms Distress (MSD) Score measures the average distress associated with menstrual symptoms. It is calculated using the MEDI-Q total score divided by MS, considering only symptoms that worsen during menstruation compared to intermenstrual days. The MSD score ranges from 0 to 5, with higher values indicating greater distress during menstruation. (D) Menstrual Specificity Index (MESI) measures the proportion of symptoms that cause more distress during menstruation compared to both intermenstrual and premenstrual phases. It is determined by identifying symptoms where distress levels are higher during menstruation (B > D and B > C) and dividing by the total number of symptoms (MS). The MESI score ranges from 0 to 1, where 0 indicates that menstrual distress is similar, while 1 signifies that all reported symptoms cause greater distress specifically during menstruation. MEDI-Q Total Score is obtained from the sum of all the distress scores calculated for each item. The minimum score obtainable is 0 and the maximum score is 125. Menstrual Symptoms (MS) Score reflects the total number of symptoms that generate distress more during menstruation than in intermenstrual days. It is obtained from the total number of symptoms that generate distress more during menstruation than in intermenstrual days. It is represented by the number of items for which the score obtained in sub-item (B) is greater than that in sub-item (D). Menstrual Symptoms Distress (MSD) Score measures the average distress associated with menstrual symptoms. It is calculated using the MEDI-Q total score divided by MS, considering only symptoms that worsen during menstruation compared to intermenstrual days. The MSD score ranges from 0 to 5, with higher values indicating greater distress during menstruation. Menstrual Specificity Index (MESI) measures the proportion of symptoms that cause more distress during menstruation compared to both intermenstrual and premenstrual phases. It is determined by identifying symptoms where distress levels are higher during menstruation (B > D and B > C) and dividing by the total number of symptoms (MS). The MESI score ranges from 0 to 1, where 0 indicates that menstrual distress is similar, while 1 signifies that all reported symptoms cause greater distress specifically during menstruation. Prior to statistical testing, the research variables were clearly defined. The primary dependent variables in this study were the four MEDI-Q outcomes: the MEDI-Q Total Score, MS Score, MSD Score, and the MESI. The independent variables included sociodemographic characteristics (age, educational degree, and occupational status) as well as clinical and menstrual history (history of contraceptive use, type of contraception, and history of reproductive or psychiatric diseases). Descriptive statistics were used to summarize patient characteristics and for some outcome parameters. To examine the relationships between the independent and dependent variables, specific statistical tests were applied. Prior to inferential statistical testing, the normality of the data distribution was assessed using the Kolmogorov–Smirnov test. Because the numeric variables (age and MEDI-Q scores) were not normally distributed, thus the association between age and menstrual distress was analyzed using the Pearson correlation coefficient with bootstrap. Other variables such as educational background, occupational status, contraceptive use history, type of contraceptive, and reproductive history were categorical data. Therefore, bivariate analysis with non-parametric statistical methods, specifically the Mann–Whitney U test, were employed to examine the relationships between the MEDI-Q scores and these categorical variables of interest. All statistical analyses were performed using IBM SPSS Statistics for Windows, Version 26.0.

This study is the first to assess menstrual distress among reproductive women in Indonesia, offering a unique contribution to the existing body of research on menstrual health, particularly in Southeast Asia. The large sample size of 930 participants enhances the generalizability and robustness of the findings, providing a comprehensive perspective on menstrual distress across various sociodemographic groups. Notably, the questionnaire used in this study was validated beforehand, ensuring strong measurement power and reliability of the collected data. However, several limitations must be acknowledged. First, as a cross-sectional study, it captures data at a single point in time, limiting the ability to draw causal conclusions. Second, our online recruitment strategy, which utilized Google Forms distributed via social media, may have introduced significant selection bias. This digital recruitment resulted in a sample with high educational attainment (74.3% vocational degree or above) and high employment rates (77.6%), which deviates from the broader Indonesian demographic profile. Consequently, our findings primarily represent a younger, more digitally engaged, and higher socioeconomic stratum. These results may not be generalizable to women from lower socioeconomic backgrounds, older age groups, or those residing in areas with limited digital and educational infrastructure. Third, while the MEDI-Q is a validated and sufficient tool for capturing the subjective multidimensional experience of menstrual distress, its reliance on self-reported data introduces potential recall and social desirability biases. Importantly, because both reproductive and psychiatric histories were based entirely on self-report without clinical verification, the diagnostic accuracy of these conditions is limited in this study. Detailed and verifiable contraceptive histories also could not be reliably ascertained; consequently, our analysis was limited to broad categorical classification (hormonal vs non-hormonal), reducing the ability to evaluate method-specific associations with menstrual distress and potentially obscuring heterogeneity in effects. Finally, while retaining participants with underlying reproductive and psychiatric disorders reflects a real community setting, the lack of multivariable adjustment for these major confounding variables limits our ability to isolate their independent effects on menstrual distress. Future studies should address these limitations by employing longitudinal designs, using objective clinical measurements to verify medical histories through clinical records or using prospective daily diaries over several cycles, to supplement the subjective data provided by the MEDI-Q. Despite these limitations, the MEDI-Q's ability to profile specific symptom domains makes it a highly usable tool for future longitudinal studies and clinical screenings to identify women at risk for severe menstrual distress. Future studies should also employ multivariate analyses to isolate the independent effects of these clinical and sociodemographic factors on menstrual distress.

This study highlights the significant impact of menstrual distress on reproductive-aged women. Age, educational background, occupational status, contraceptive use, and history of reproductive and psychiatric disorders were identified as key determinants. These findings underscore the importance of integrated menstrual health education and early screening for psychiatric and reproductive comorbidities. Early identification and targeted interventions are essential to improve women’s quality of life, and future research should assess effective strategies to reduce menstrual distress. Integrating menstrual health assessment into primary care and workplace wellness programs may mitigate distress and improve quality of life.

Menstrual distress exerts a significant negative impact on multiple domains of women's daily functioning. To effectively capture these complex associations, the use of a multidimensional instrument like the MEDI-Q is essential. While traditional clinical assessments often focus on physiological markers, the MEDI-Q provides a more holistic representation of the patient's lived experience, offering high usability for both research and clinical practice. Its comprehensive structure allows tailored-individualized interventions and monitoring long-term treatment outcomes in women with menstrual disorders [ 2 , 11 , 17 ]. In this cross-sectional, online-based study of 930 reproductive women, we identified a significant association between menstrual distress and several sociodemographic and clinical variables. Our study showed that the mean age of participants was 31.57 ± 6.89 years old, in line with a study by Vannuccini et al., which reported that most of their participants (32.8%) were between the ages of 25 and 35. [ 11 ] The mean of age at menarche in our study was 13.07 ± 1.668.There has been a trend of a lower average age at menarche in high-income countries due to many factors, such as, genetic, lifestyle changes, previous health and nutrition status, community culture and the environment. A longitudinal study conducted in Indonesia over a 50-year period (1961 to 2010) demonstrated a decline in the mean age at menarche from 14.43 years to 13.63 years. Furthermore, the study projected a decrease in the average age at menarche by approximately 8 to 9 days annually [ 18 ]. Regarding menstrual health, most participants reported having a regular menstrual cycle interval (81.4%) and duration (85.5%), these results were similar as Park et al. study, which shows that 51.1% participants reported a regular menstrual cycle, with most of it reported the frequency between 21–35 days (93%) and normal duration 2–7 days (95.2%) among of all the participants. [ 19 ] In our study, the highest mean distress scores were observed for lower abdominal pain, sadness, feeling of being impure, muscle/osteoarticular pain, and emotional lability, consistent with previous reports that identified these symptoms as having the greatest severity [ 11 , 20 ]. These findings indicate that menstrual distress has a broad impact, affecting both the physical and psychological domains of health. Lower abdominal pain associated with dysmenorrhea is believed to result from the overproduction of uterine prostaglandins (PGs), typically PGF 2a and PGE 2 , that could lead to myometrial hypercontractility and restrict the blood flow. Hypoxia in the uterine muscle then causes lower abdominal pain [ 21 ]. Menstrual pain sometimes manifests as a form of dull splanchnic pain, a non-localised and often hard-to-describe pain site. Such pain might also be felt in bones, muscles, and skin around organs, thus creating muscle/osteoarticular pain [ 22 ]. Dysmenorrhea is also associated with a higher level of depression, mood swings, worries, fears, and anxiety. A significant association was found between primary dysmenorrhea and mood disorder, problems with self-concept, feelings of guilt, rejection, and even suicidal thoughts. Not only that, the frequency and severity of dysmenorrhea were correlated with feelings of loneliness and interpersonal problems; thus, in turn, can reduce the overall well-being and cause distress [ 23 ]. To fully understand the implications of our findings, it is essential to contextualize that these results within the unique socio-cultural landscape of Indonesia. In Indonesian society, menstrual pain and distress are frequently normalized as an inherent part of womanhood—often culturally perceived as a woman's destiny. This cultural normalization significantly shapes health-seeking behaviors, where women tend to endure the pain, underreport their symptoms to medical professionals, and delay clinical interventions [ 24 ]. Consequently, instead of seeking medical care, a substantial proportion of Indonesian women prefer self-management strategies, including a heavy reliance on traditional herbal medicines, particularly  'jamu kunyit asam' (a turmeric and tamarind-based botanical drink), which is culturally deeply rooted and scientifically documented as a prevalent first-line remedy for managing dysmenorrhea in Indonesia [ 25 ]. This dichotomy where medical management of menstruation is highly accessible to some but culturally restricted for others, likely contributes to the variability observed in the MEDI-Q scores across different demographic groups in our study. Ultimately, these distinct cultural beliefs and health-seeking behaviors underscore the necessity for culturally sensitive, targeted clinical screening tools like the MEDI-Q in the Indonesian healthcare system.

According to our research, educational background has been associated with higher MS scores (Z: −2.230, p < 0.05), with participants from higher educational backgrounds reporting more severe physical symptoms. In our study population, a significant majority of participants (n = 691; 74.3%) possessed a vocational degree or higher, while a smaller proportion (n = 239; 25.7%) had a high school education or lower. While not reaching statistical significance, a similar trend was observed for the MEDI-Q Total Score (Z: −1.443; 4.00 vs. 3.00). Interestingly, the MSD score showed an inverse pattern, where scores were higher among participants with a high school education or lower (Z: −0.243; 1.33 vs. 1.25) and the MESI results were nearly identical across both educational groups (Z: −0.622), suggesting that educational background does not influence the specificity of symptoms to the menstrual phase. Previous studies indicate that women with higher educational attainment are better equipped to manage menstrual health issues effectively, as increased education is associated with greater knowledge, broader access to resources, and a higher likelihood of adopting self-care and professional therapeutic interventions [ 33 ]. Conversely, research also demonstrates that lower educational attainment is often correlated with more precarious employment, elevated stress levels, and increased menstrual distress, resulting in higher perceived distress scores among this group [ 34 , 35 ]. However, the evidence supporting the relationship between academic factors and menstrual outcomes remains limited, and it is important to note potential bias, as women with higher education levels may report menstrual complaints more readily due to greater awareness of menstrual health issues and lower education group might reflect different socio-economic stressors or varying access to coping resources. The representativeness of our study population must be carefully considered as the high prevalence of vocational degrees or higher (74.3%) in our sample is significantly higher than the Indonesian national average. This indicates that our sample is skewed toward a higher socioeconomic stratum. While this provides insights into the experiences of educated women, it may not fully capture the challenges faced by women in lower socioeconomic groups or rural areas with limited educational access.

Women of reproductive age are susceptible to disruptions in daily functioning due to menstrual distress, which manifests through a range of adverse physical and psychological symptoms [ 1 , 2 ]. Women of reproductive age, typically defined as individuals between 15 and 49 years old, regardless of marital status, including those who are married, widowed, or never married, constitute a significant demographic, comprising approximately 52% of the population globally, and 47.9% in Indonesia [ 1 – 4 ]. Menstrual distress incidence among women of reproductive age is notably high, affecting up to 19% of the population, with affected individuals also demonstrating an increased susceptibility to psychological symptoms [ 5 ]. In Indonesia, 13.7% of women of reproductive age experiences menstrual cycle irregularities and 64.3% experiences dysomenorrhea [ 6 , 7 ]. The most common physical symptoms of menstrual distress are abdominal pain, backache, fatigue, bloating, and tenderness of the breasts, while the most common psychological symptoms are hopelessness, stress, irritability, and food cravings [ 8 – 10 ]. Menstrual distress should be distinguished from normal stress responses, which are commonly conceptualized as eustress [ 11 ]. Eustress represents a positive reaction to a stressor, which aims to make the individual adapt well to menstrual changes. A key distinguishing characteristic of menstrual distress is its significant impairment of daily functioning, including social, mental, and occupational domains [ 11 , 12 ]. Studies have reported that productivity loss while attending work or school affects up to 80.7% of reproductive-age women experiencing menstrual distress, while absenteeism due to menstrual distress reaches 13.8% [ 12 ]. Additionally, research has demonstrated a strong correlation between high levels of menstrual distress and a reduced quality of life [ 11 ]. Given its substantial physical and psychological impact and its potential to reduce quality of life, menstrual distress requires greater attention. Identifying the factors associated with menstrual distress among reproductive-age women is crucial for facilitating early diagnosis and implementing effective management strategies. A robust assessment tool is essential to evaluate subjects’ quality of life, pain scores, and perceived stress levels to gain a comprehensive understanding of the factors associated with menstrual distress. The Menstrual Distress Questionnaire (MEDI-Q) has been introduced as a comprehensive tool for assessing menstrual distress and its impact on an individual's functioning. Additionally, this questionnaire accounts for symptom frequency and differentiates between menstrual, intermenstrual, and premenstrual phase-related symptoms, offering a more refined and precise evaluation of menstrual distress.The MEDI-Q is easily administered through both local and online platforms and features a user-friendly interface. Additionally, it has undergone a rigorous validation process to ensure its accuracy and reliability [ 11 ]. Given its robustness and reliability, the MEDI-Q is a valuable tool for investigating factors associated with menstrual distress among reproductive-age women based on an online survey. However, there remains a lack of robust data on the impact of menstrual distress in Southeast Asia, and evidence specifically for Indonesia is scarce. Indonesia’s population is unique due to diverse cultural beliefs, a wide variety of contraception choices, and distinct health-seeking behaviors that shape menstrual health outcomes. These factors, coupled with prevailing stigma and economic imbalance among the population, highlight the complexity and research gaps in menstrual health for Indonesian women [ 13 – 16 ]. Therefore, this study aimed to investigate factors associated with menstrual distress among reproductive-age women based on the MEDI-Q online survey and analyze the factors influencing menstrual distress scores, discomfort scores of menstrual symptoms during the intermenstrual phase, and the proportion of symptom exacerbation during the menstrual phase in comparison to the premenstrual and intermenstrual phases.

The MEDI-Q Total Score and MS were found to be significantly correlated with occupational status in our study. Specifically, employed participants demonstrated higher scores (Z: –2.245 and –2.720, respectively). In our sample, a vast majority of the participants were employed (n = 722; 77.6%), while a smaller proportion were unemployed or not working (n = 208; 22.4%). While the MSD and MESI scores did not reach statistical significance, they exhibited a similar trend, being notably higher among employed women (Z: −1.108 and −1.087, respectively). This consistent pattern across all domains suggests that employment-related factors may universally exacerbate the perception of menstrual distress. Occupational factors, particularly psychosocial elements such as job stress, social support at work, and working in shifts, may play a role in the prevalence of menstrual irregularities among female employees [ 36 ]. The menstrual cycle is regulated by hypothalamic gonadotropin-releasing hormone (GnRH), but can be inhibited by hypothalamic–pituitary–adrenal (HPA) axis in response to stressors, potentially affecting menstrual cycle disorders or pain syndrome in female workers [ 37 ]. Another study linked negative menstruation-related symptoms to high job stress and poor mental health. This finding suggests that compromised physical and mental recovery, diminished sleep quality, and the presence of health problems can be directly impacted by poor mental health, which increases sensitivity to hormonal fluctuations and leads to symptoms experienced both prior to and during menstruation among female workers [ 38 ]. However, the high percentage of employed participants (77.6%) in this study must be addressed in terms of representativeness. This employment rate is significantly higher than the national female labor force participation rate in Indonesia, which historically fluctuates around 53.34–55.41% [ 39 ]. This suggests that our study population predominantly represents women in the formal sector or urban employment, who may face different types of stressors compared to women in the informal or agricultural sectors. While our results provide a robust profile of menstrual distress among working women, they should be interpreted as being representative of a specific, higher socioeconomic group rather than the general Indonesian female population.