Understanding Menstrual Irregularities in Adolescents: Key Factors and Their Role in Achieving Sustainable Development Goals

Understanding Menstrual Irregularities in Adolescents: Key Factors and Their Role in Achieving Sustainable Development Goals | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Understanding Menstrual Irregularities in Adolescents: Key Factors and Their Role in Achieving Sustainable Development Goals Sendhi Tristanti Puspitasari, Ferry Fadzlul Rahman, Fahni Haris, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5538953/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Menstrual health issues such as irregular menstruation and secondary amenorrhea can have a substantial impact on adolescent well-being. Since girls' reproductive health is crucial to global strength, the Sustainable Development Goals and United Nation Youth 2030 prioritize safe and dignified menstruation management. Despite the widespread recognition of numerous factors contributing to the risk of menstrual irregularities, this study investigated prevalence of menstrual irregularities among adolescents in Malang City, Indonesia, and to determine whether stress, depression, dietary intake, and physical activity are significant predictors of these irregularities. Method A cross-sectional study was conducted using cluster sampling and questionnaires to collect data from 482 adolescents across five sub-districts in Malang City. Bivariate analyses, t-tests, chi-square tests, and logistic regression were performed using SPSS to identify factors associated with menstrual irregularities. Results Menstrual irregularities were reported by 16% of respondents. Adolescents with regular cycles were significantly older than those with irregular cycles (p = 0.044, Mean ± SD: 16.24 ± 1.11). Secondary amenorrhea occurred in 8.4% of respondents with regular cycles (p < 0.001 ). Severe depression was present in 41% of those with irregular cycles compared to 28.3% with regular cycles (p = 0.004). A history of secondary amenorrhea was the strongest predictor of irregular cycles (OR = 5.509), with age and protein intake also contributing. Conclusion In conclusion, age, protein intake, and depression significantly predict menstrual irregularities among adolescents in Malang City, Indonesia. Targeted interventions focusing on dietary education and mental health support could improve adolescent menstrual health and overall well-being. Future research should evaluate the effectiveness of these interventions. These findings show that adolescents need tailored dietary and mental health interventions to improve menstrual health and sustained growth. menstrual health menstrual irregularities sustainable development goal adolescents dietary patterns psycho-social issues Figures Figure 1 INTRODUCTION A holistic approach to menstrual health and sexual reproductive health can give girls, and women the knowledge, skills, support, and resources they need to thrive. Menstrual health is essential to achieving a world where every pregnancy is wanted, every childbirth is safe, and every young person's potential is fulfilled. Moreover, the Sustainable Development Goals and United Nation Youth 2030 include supporting girls, and women to manage menstruation safely and with dignity ( 1 ). The reproductive health of adolescent girls is a source of world strength because the global youth population is expected to be 15% of the population by 2030, or 1.3 billion out of 8.5 billion. If global sustainable development is not accelerated, many young people will suffer from starvation, disease, dropping out of school, poverty, and air pollution ( 2 ). Menstrual health is closely connected to achieving several Sustainable Development Goals (SDGs). SDG 3 emphasizes universal access to sexual and reproductive healthcare services, including education on menstrual health management. Furthermore, menstrual health directly impacts adolescents' school attendance and academic performance—issues central to achieving SDG 4 (quality education). Adolescents experiencing menstrual irregularities may face increased school absenteeism, reduced academic engagement, and impaired performance, highlighting the critical need for effective menstrual health management. Additionally, ensuring menstrual health aligns closely with SDG 5, which aims for gender equality and empowerment of women and girls by addressing health-related barriers to their full participation in society ( 1 , 2 ). Despite global awareness, Menstrual disorders, such as secondary amenorrhea and irregular menstrual cycles, can significantly impact the quality of life, daily activities, and academic performance of female adolescents ( 3 ). secondary amenorrhea due to its significant impact on adolescent reproductive health, potential long-term consequences, and its role as an indicator of underlying stress, dietary, or physical activity issues common in urban settings ( 3 ). Secondary amenorrhea, affecting approximately 20% of women with ovulatory dysfunction, is an early indicator of reproductive health issues ( 4 , 5 ). It is defined as the absence of menstruation for three consecutive months in females aged 12 to 49 ( 6 ). Various factors, including pregnancy, significant weight changes, strenuous exercise, elevated prolactin levels, and stress, can lead to secondary amenorrhea ( 7 , 8 ). Untreated, it can result in infertility or difficulties in conception ( 8 ). The prevalence of secondary amenorrhea varies globally. Previous studies have shown that only 10–15% of women experience regular 28-day cycles, with menstrual durations of 3–7 days ( 9 , 10 ). Irregular menstruation can also lead to secondary amenorrhea. Stress, dietary patterns, physical activity, body mass index (BMI), depression, and hormonal imbalances contribute to menstrual irregularities ( 10 ). In Pakistan, Kafael reported a secondary amenorrhea prevalence of 44.8% among students ( 11 ), whereas a study in Indonesia found that 28.0% of 242 medical students experienced secondary amenorrhea ( 12 ). Recent evidence underscores the role of chronic psychosocial stress among urban adolescents, characterized by intense academic pressures, rapid urbanization, and socio-economic disparities (( 13 )). This stress-induced elevation of cortisol levels may disrupt the HPG axis, highlighting the importance of examining stress as a potential contributor to menstrual irregularities despite mixed empirical results. additionally, physical activity has emerged as a nuanced factor affecting menstrual regularity among urban adolescents. While moderate physical activity supports menstrual health by maintaining hormonal balance, extreme physical exertion or prolonged sedentary behavior can lead to significant menstrual disruptions, thus warranting detailed examination in adolescent populations (( 14 )) Factors contributing to menstrual irregularities may vary across countries. In a study of 200 Indonesian high school students, Aryani found that 24.5% had irregular cycles. However, this was not significantly influenced by BMI, age, age at menarche, nutritional status, physical activity, or fat intake ( 13 ). Pratami et al. discovered that 86.3% of female Indonesian Navy cadets had menstrual disorders, with 29.6% experiencing secondary amenorrhea. Heavy exercise (96.8%) and low-stress levels (76.8%) were also significant factors ( 14 ). Nutritional intake plays a critical role in maintaining regular menstrual cycles. Diets rich in protein, plant-based fats, and high-fiber carbohydrates provide the body with essential nutrients for hormone production ( 15 ). However, vegetarian diets may affect protein intake, lacking essential amino acids and phytoestrogens, which could have anti-estrogenic effects ( 16 ). Dietary patterns, a key determinant of menstrual health, are deeply rooted in cultural and regional contexts. In Indonesia, a predominantly plant-based diet, featuring tofu and Tempe as protein staples, introduces unique nutritional factors that may influence hormonal regulation ( 18 ). This dietary context, combined with limited access to mental health resources and nutrition education, creates a distinct environment for menstrual health challenges ( 12 ). Malang City, a rapidly urbanizing region, exemplifies this intersection of traditional dietary habits and modern lifestyle pressures. Therefore, exploring dietary patterns specifically among adolescents in rapidly urbanizing regions like Malang City, where traditional plant-based dietary habits intersect with increasing consumption of processed foods is particularly important. Clarifying how these localized dietary factors, together with psychosocial and physical activity conditions, influence menstrual irregularities will help tailor region-specific interventions that align closely with the real-life context of Indonesian adolescents. Despite growing attention to menstrual health among adolescents globally, the unique lifestyle and dietary patterns of the Indonesian population, which is also one of the world's developing countries, this study aims to determine the prevalence of menstrual irregularities among adolescents in Malang City and explore the relationships between these irregularities and associated factors, such as dietary intake, stress, and physical activity. This study addresses these gaps by concurrently investigating stress, depression, dietary intake, and physical activity as combined predictors of menstrual irregularities, providing essential insights for targeted local interventions aligned with Sustainable Development Goals (SDGs) METHODS Study design, settings, and participants This study employed a cross-sectional design, suitable for assessing the prevalence of menstrual irregularities and their associated factors among adolescents in Malang City, Indonesia. The Health Research Ethics Committee at the University of Muhammadiyah Malang approved the research (Certificate No.E.5.a/181/KEPK-UMM/X/2019), and informed consent was obtained from all participants. The study adhered to ethical standards, ensuring participant confidentiality and sensitivity in handling menstrual health data. Sample size and sampling procedures Figure 1 defined cluster sampling was employed to ensure diverse representation from different sub-districts within Malang City, capturing a broad spectrum of socio-demographic factors. The sample size was calculated based on an assumed prevalence of menstrual irregularities among adolescents ( 19 ), with a 95% confidence interval, resulting in a target sample of 529 respondents. After initial screening and data cleaning, completed questionnaires from 482 students were included for analysis. Questionnaire Variables The study utilized validated and reliable questionnaires to assess various variables, including stress levels, depression, nutrition frequency, physical activity, sociodemographic data, and self-reported menstrual characteristics. Psychological factors were measured using the Perceived Stress Scale (PSS) and Beck Depression Inventory – II questionnaire (BDI-II), both of which are well-suited for adolescent populations. Menstrual health and cycle definition Menstrual health is a state of complete physical, mental, and social well-being and not merely the absence of disease or infirmity to the menstrual cycle, in which women, girls and all people who menstruate experience a positive and respectful environment, free from stigma and psychological distress, with the resources and support they need to care for their bodies confidently and make informed decisions about self-care throughout the life course; and the freedom to decide whether and how to participate in all spheres of life, including civil, cultural, economic, social, and political, free from menstrual-related exclusion, restriction, discrimination, coercion, and or violence ( 1 ). Menstrual cycle regularity was classified based on the International Federation of Gynecology and Obstetrics (FIGO) standards (2018), where a regular cycle was defined as occurring every 24–38 days without secondary amenorrhea in the preceding three months. Predictors Body Mass Index (BMI) was calculated based on self-reported height and weight data and classified into underweight (BMI 24.5) ( 20 ). Stress levels were assessed using the PSS, with respondents categorized into mild, moderate, and severe stress based on their scores. Depression was measured using the BDI, with scores categorized into mild (0–19) and severe (> 20) depression. Nutritional intake was assessed using a modified Food Frequency Questionnaire (FFQ), and physical activity was evaluated using the International Physical Activity Survey (IPAQ). The Perceived Stress Scale (PSS) is a seven-item psychological self-report test with multiple-choice answers. It was divided into three groups based on the PSS score: mild ( 1 – 14 ), moderate ( 15 – 26 ), and severe (more than 26) ( 21 ). Adapted from Ginting, 2013, the Beck Depression Inventory (BDI) questionnaire was used to determine depression levels ( 22 ). Researchers in this study re-categorized the outcomes into two groups: mild depression group (0–19) and severe depression group (> 20). The Perceived Stress Scale (PSS) and Beck Depression Inventory (BDI) were selected for this study due to their widespread use in adolescent populations and their ability to capture the psychological dimensions relevant to menstrual health. This survey used a modified FFQ (Food Frequency Qualitative) questionnaire validated for the Indonesian population. Food items were grouped into five categories: carbohydrates, fats, proteins, fiber-containing foods, and snacks. Consumption frequency was divided into two categories: “sufficient” if eaten 3–4 times daily, and “less” if eaten ˂ 3 times daily. The frequency score was calculated by the total number of times each respondent consumed the food and then divided by the total number of respondents based on the original survey ( 23 ). Short-form questionnaires from the International Physical Activity Survey (IPAQ), revalidated by Amelia in 2009, Explicitly clarified and cited the validation of IPAQ short-form for Indonesian populations were used to determine the respondents’ physical activity. Frequencies of heavy and moderate physical activity were measured. Three levels were defined for heavy physical activity: low (20 hours per week), middle (20–89 hours per week), and high (> 90 hours per week), and moderate physical activity: low (less than 50 minutes per week), middle (between 50 and 70 minutes per week), and high (more than 70 minutes per week) ( 24 ). Data analysis Data were analyzed using SPSS version 25. Descriptive statistics were used to summarize categorical variables as frequencies and percentages, and continuous variables as means and standard deviations. Bivariate analyses ( t-test and chi-square ) were conducted to explore relationships between independent variables and menstrual irregularities, Cases with missing values on key variables were excluded using listwise deletion. Only respondents with complete data across all variables of interest were included in the final analysis (n = 482). Effect sizes were reported using odds ratios (ORs) with 95% confidence intervals from logistic regression analyses to quantify the strength of association between predictors and menstrual irregularitie s . Logistic regression was used to identify significant predictors of menstrual cycle irregularity, with a significance threshold set at p < 0.05. A stepwise logistic regression analysis was performed using backward elimination based on a p-value threshold of 0.10 to retain meaningful predictors while improving model parsimony. Multi-collinearity was assessed using the Variance Inflation Factor (VIF), and all included variables had VIF values < 2. Odds ratios (OR) with 95% confidence intervals (CI) were reported. Additionally, a ΔOR column was included to show the percentage change in OR values across model iterations RESULTS Socio-demographic characteristic A total of 482 respondents completed the questionnaires, among which 16.2% (n = 78) reported irregular menstrual cycles, while 83.8% (n = 404) had regular cycles. The ages of the respondents ranged from 14 to over 19 years (Mean ± SD: 16.24 ± 1.11). The majority of participants in the irregular menstrual cycle group were aged between 14 and 16 years (67.95%), whereas participants with regular menstrual cycles were significantly older (p = 0.044). The mean age of menarche for all respondents was 12.41 years. Table 1. The distribution of respondents by age, menarche age, menstrual cycle characteristics, and menstrual cycle Menstrual Cycle Characteristics Menstrual Cycle OR (95% CI) P value Regular Irregular N % N % Age 14-16 17-19 >19 213 190 1 52.7% 47% 0.3% 53 25 0 68% 32% 0% - 0.044* Mean ± SD 16.24 ± 1.117 Min – Max 14 – 20 Age of Menarche Mean ± SD Min – Max 12.41 ± 1.127 9-16 History of secondary amenorrhea No Yes 370 34 91.6% 8.4% 51 27 65.4% 34.6% 5.761 p < 0.001 * History of taking medicine No Yes 389 15 96.3% 3.7% 75 3 96.2% 3.8% - 0.955 History of the family for secondary amenorrhea No Yes 402 2 99.5% 0.5% 76 2 97.4% 2.6% - 0.125 *p < α, α = 0.05 with chi-square test Additionally, 91.6% of respondents with regular cycles and 65.4% with irregular cycles did not have a history of secondary amenorrhea. Similarly, 96.3% of respondents with regular cycles and 96.2% with irregular cycles reported no history of medication use. A significant connection between secondary amenorrhea and the menstrual cycle (p = p < 0.001 , OR = 5.761) was found. This shows that people with a history of secondary amenorrhea are 5.761 times more likely to have irregular menstrual cycles. However, this statistical test indicated a lack of significance between medicine use (p = 0.955) and family history of secondary amenorrhea (p = 0.125) with menstruation. Factors associated with menstrual irregularity. Stress and Depression The results showed that 89.6% of respondents with regular cycles and 84.6% of those with irregular cycles experienced moderate stress. No significant relationship was found between stress and menstrual irregularities (p = 0.312). Table 2. The distribution of respondents by stress, depression, and menstrual cycle Risk Factor Category Menstrual cycle OR (95% CI) p-value Irregular (n, %) Regular (n, %) Depression Severe 32 (41%) 107 (28.3%) 1.931 0.009* Mild 46 (59%) 297 (71.7%) Ref Stress Moderate 66 (84.6%) 361 (89.6%) 0.655 0.312 Mild 12 (15.4%) 43 (10.4%) Ref *p < α, α = 0.05 with a chi-square test However, depression was significantly associated with menstrual irregularity (p = 0.009). Respondents with severe depression were 1.931 times more likely to experience irregular menstrual cycles than those with mild depression (OR = 1.931). Table 3. The distribution of respondents by a sedentary lifestyle, physical activity, and menstrual cycle Risk Factor Category Menstrual Cycle OR (95% CI) p-value Irregular (n, %) Regular (n, %) Heavy Physical Activity High 22 (28.2%) 87 (21.5%) 1.431 0.254 Low 56 (71.8%) 317 (78.5%) Ref Moderate Physical Activity High 70 (88.6%) 346 (85.6%) 1.467 0.433 Low 8 (11.4%) 58 (14.4%) Ref Sedentary Lifestyle High 49 (63.8%) 251 (63.1%) 1.030 0.908 Enough 29 (37.2%) 153 (37.9%) Ref *p < α, α = 0.05 with chi-square test In both the regular and irregular menstrual cycle groups, a high proportion of respondents engaged in moderate physical activity (78.5% and 71.8%, respectively). However, no significant relationship was observed between physical activity, sedentary lifestyle, and menstrual cycle irregularity (p = 0.908; p = 0.254; p = 0.433, respectively). Table 4. The distribution of respondents by BMI, nutritional intake, and menstrual cycle Risk Factor Category Menstrual cycle OR (95% CI) p-value Irregular (n, %) Regular (n, %) Protein Intake Less 34 (43.6%) 98 (24.3%) 0.414 p < 0.001 * Sufficient 44 (56.4%) 306 (75.7%) Ref Fiber Intake Less 24 (30.8%) 78 (19.3%) 0.538 0.023* Sufficient 54 (69.2%) 326 (80.7%) Ref Fat Intake Sufficient 22 (28.2%) 97 (24%) 1.243 0.431 Less 56 (71.8%) 307 (76%) Ref Carbohydrate Intake Less 55 (70.5%) 276 (68.3%) 0.902 0.902 Sufficient 23 (29.5%) 128 (31.7%) Ref Snack Intake Sufficient 28 (35.9%) 138 (34.2%) 1.079 0.767 Less 50 (64.1%) 266 (65.8%) Ref BMI Overweight 8 (10%) 45 (11.2%) - 0.766 Normal 49 (63%) 236 (58.4%) Underweight 21 (27%) 123 (30.4%) Ref *p < α, α = 0.05 with chi-square test Respondents with irregular menstrual cycles had the following nutritional patterns: 63% had normal BMI, 70.5% had insufficient carbohydrate intake, 56.4% had sufficient protein intake, and 69.2% had sufficient fiber intake. A significant relationship was found between menstrual cycle regularity and both protein (p = p < 0.001 ) and fiber intake (p = 0.023). Respondents with sufficient protein intake had a 58.6% lower likelihood of experiencing irregular menstrual cycles compared to those with insufficient intake (OR = 0.414, 95% CI: 0.303–0.849). Similarly, those with sufficient fiber intake had a 46.2% lower likelihood of irregular cycles (OR = 0.538, 95% CI: 0.318–1.072 . Table 5. Bivariate Selection Variable P value Age History of secondary amenorrhea History of taking medicine History of the family for secondary amenorrhea Stress Depression Sedentary lifestyle Heavy physical activity Moderate physical activity BMI Carbohydrate Protein Fat Fiber Snack 0.002* p < 0.001 * 0.871 0.250 0.180 0.006* 0.249 0.271 0.213 0.775 0.866 0.007* 0.093 0.083 0.591 *p value < 0.05 Table 6. Logistic regression modeling Variable B SE p-value OR ∆ OR 95% CI Lower Upper 1 st Model Age History of secondary amenorrhea Stress Depression Sedentary lifestyle Moderate physical activity Protein Fat Fiber -0.853 1.687 -0.569 0.819 -0.289 0.609 -0.758 0.529 -0.574 0.293 0.318 0.399 0.290 0.284 0.436 0.290 0.316 0.312 0.004 p < 0.001 0.154 0.005 0.309 0.163 0.009 0.094 0.066 0.426 5.406 0.566 2.268 0.749 1.838 0.469 1.698 0.563 - - - - - - - - - 0.241 2.903 0.415 1.292 0.427 0.834 0.267 0.927 0.307 0.760 10.046 1.343 4.072 1.295 2.200 0.832 3.191 1.039 2 nd Model Age History of secondary amenorrhea Stress Depression Moderate physical activity Protein Fat Fiber -0.821 1.673 -0.588 0.823 0.555 -0.732 0.501 -0.556 0.292 0.317 0.399 0.290 0.434 0.289 0.314 0.311 0.005 p < 0.001 0.140 0.005 0.200 0.011 0.111 0.074 0.440 5.329 0.555 2.278 1.743 0.481 1.651 0.573 3.28% 1.4% 1.9% 0.43% 5.45% 2.55% 2.84% 1.77% 0.250 2.866 0.412 1.297 0.811 0.276 0.903 0.313 .783 9.882 1.339 4.091 2.129 .852 3.089 1.058 3 rd Model Age History of secondary amenorrhea Stress Depression Protein Fat Fiber -0.800 1.691 -0.547 0.823 -0.703 0.479 -0.538 0.291 0.316 0.398 0.289 0.287 0.314 0.310 0.006 p < 0.001 0.170 0.004 0.014 0.127 0.083 0.449 5.424 0.579 2.277 0.495 1.615 0.584 0.02% 1.7% 4.32% 0.04% 2.91% 2.23% 1.9% 0.256 2.909 0.423 1.290 0.282 0.883 0.318 0.799 10.009 1.362 4.058 0.868 3.014 1.072 4 th Model Age History of secondary amenorrhea Depression Protein Fat Fiber -0.811 1.682 0.765 -0.716 0.511 -0.519 0.290 0.314 0.283 0.285 0.311 0.309 0.005 p < 0.001 0.007 0.012 0.101 0.093 0.444 5.374 2.149 0.489 1.667 0.595 1.12% 0.93% 5.95% 2.04% 3.21% 1.88% 0.252 2.903 1.233 0.279 0.905 0.325 0.785 9.948 3.744 0.855 3.070 1.091 5 th Model Age History of secondary amenorrhea Depression Protein Fiber -0.772 1.701 0.743 -0.644 -0.472 0.288 0.312 0.281 0.280 0.305 0.007 p < 0.001 0.008 0.021 0.122 0.462 5.477 2.103 0.525 0.624 4.0% 1.9% 2.18% 7.36% 4.86% 0.263 2.973 1.212 0.303 0.343 0.813 10.091 3.650 0.908 1.135 6 th Model Age History of secondary amenorrhea Depression Protein -0.742 1.706 0.793 -0.704 0.286 0.310 0.278 0.276 0.010 p < 0.001 0.004 0.011 0.476 5.509 2.209 0.495 1.08% 0.58% 5.04% 6.06% .271 3.001 1.280 .288 0.835 10.114 3.813 0.849 Logistic regression analysis identified significant predictors of menstrual cycle irregularity. The final model included age, history of secondary amenorrhea, depression, and protein intake. A history of secondary amenorrhea was the strongest predictor of menstrual irregularities, with an odds ratio (OR) of 5.509 and a 95% confidence interval (CI) of 2.973–10.091, indicating a significantly higher risk among those with a history of amenorrhea. Other significant factors included depression and protein intake. DISCUSSION This study aimed to examine the prevalence and contributing factors of menstrual irregularities among adolescents, with a focus on sociodemographic, dietary, and psychological factors. Our findings add to the growing body of literature on adolescent menstrual health, highlighting the critical roles of age, nutrition, and mental health in maintaining regular menstrual cycles. Improving adolescent menstrual health may contribute to better outcomes in well-being, education continuity, and gender equity, especially when supported by broader health and social interventions. The results indicated that age and dietary intake were significant factors in menstrual regularity. Previous research has shown that menarche is influenced by body weight, protein intake, family stress, and activity levels ( 25 ). The age of menarche is a significant factor in gaining well-being as a whole ( 26 ). Furthermore, early menarche correlates with early pregnancy and certain sexually transmitted infections (STIs) in low- and middle-income countries ( 1 ). While non-genetic factors such as premature birth can also delay sexual maturity ( 27 ), our study emphasized the importance of nutrition and mental health in maintaining menstrual regularity in adolescence. Most of the participants had normal BMI, and no significant association was found between BMI and menstrual regularity, which aligns with Kulsum's findings ( 9 ). However, this contrasts with studies by Sitoayu and Nuryanti, which identified a relationship between BMI and menstrual irregularities ( 28 , 29 ). These mixed results suggest that the relationship between BMI and menstrual health may be more complex, potentially influenced by other lifestyle factors. Dietary intake, specifically protein and fiber, was strongly associated with menstrual regularity in this study. Sufficient intake of these nutrients was linked to a lower likelihood of experiencing irregular cycles, supporting previous research on the role of nutrition in hormonal regulation ( 17 , 18 ). The participants’ diets, rich in tofu, Tempe, and other protein sources, were in line with studies on vegetarian diets, which also found associations between nutrient intake and menstrual regularity ( 30 ). Protein, as a critical building block for cellular function, plays an essential role in prolonging the follicular phase, thus contributing to regular menstrual cycles ( 31 ). Interestingly, no significant associations were found between menstrual irregularities and stress, sedentary lifestyle, or BMI in this study. Depression can lead to hormonal imbalances by affecting the HPG axis, causing elevated cortisol levels that disrupt gonadotropin-releasing hormone (GnRH) production ( 32 ). This finding underscores the importance of addressing mental health in adolescents, as untreated depression can have broader implications for reproductive health ( 33 ). No significant relationship was found between physical activity and menstrual irregularities. This result is consistent with studies that did not observe significant differences in menstrual patterns based on general physical activity levels ( 34 , 35 ). However, regular physical activity is known to contribute to overall health, including maintaining a healthy weight and improving insulin sensitivity, both of which are important for menstrual regulation. While some irregular menstrual cycles may reflect normal physiological variation during adolescence, persistent irregularities can indicate underlying hormonal or health issues that may affect future reproductive health. When left unaddressed, menstrual health challenges may contribute to school absenteeism and reinforce social stigma, which in turn can limit educational opportunities and perpetuate gender-related disparities in adolescent health outcomes. The findings of this study highlight the role of traditional dietary patterns in influencing menstrual health among Indonesian adolescents. Tofu and Tempe, key components of the Indonesian diet, are rich in phytoestrogens, which can mimic estrogen in the body and potentially stabilize hormonal fluctuations ( 3 ). While similar effects of plant-based diets have been observed globally, their impact may be more pronounced in Indonesia due to the high prevalence of these foods in daily meals ( 4 ). Furthermore, the socio-economic landscape of Malang City, characterized by urbanization and limited access to healthcare services, adds a layer of complexity. Adolescents with irregular menstrual cycles often experience compounded barriers, including stigma surrounding menstruation, lack of nutritional guidance, and inadequate mental health support ( 5 ). To address these challenges, culturally tailored interventions should include school-based nutrition programs emphasizing local foods, workshops for teachers to support menstrual health education, and accessible mental health services to reduce stigma and provide counseling for adolescents ( 34 , 35 ). This study has several limitations. First, the cross-sectional design prevents causal inferences between risk factors and menstrual irregularities. Second, self-reported data on menstruation, BMI, and lifestyle behaviors may be subject to recall and reporting bias. Third, potential confounding factors such as sleep quality, socioeconomic status, and hormonal contraceptive use were not measured. By focusing on Indonesia's unique dietary and socio-cultural environment, this study contributes a regional perspective to the global discourse on adolescent menstrual health. These findings underscore the importance and diversity of integrating local context into global health strategies, ensuring that interventions are both effective and culturally appropriate. The study has significant drawbacks. The sample was limited to four senior high schools in Malang City using cluster sampling procedures, which may have underrepresented the diversity of Indonesian teenagers. Furthermore, using self-reported data on menstrual features and lifestyle factors increases the risk of memory bias or mistakes. Despite these restrictions, the researcher believes that by focusing menstrual health management in public health policies, educational programs, and economic strategies, we can ensure that everyone who menstruates can do so with dignity and without being limited in their potential. The teenagers will then have a brighter future based on human well-being, education, and gender equality (SDGs 3, 4, and 5) To validate these findings, future studies should use a larger sample size and objective indicators of menstrual health. Finally, by promoting menstrual health and equity in access to care, the study supports broader gender empowerment objectives. Although indirect, these pathways reflect how evidence-based, localized interventions can advance global health and development goals. Future research should use longitudinal designs and objective measures (e.g., stress biomarkers, activity trackers) to clarify causal links. Including factors like sleep, school stress, and healthcare access may also provide a more complete understanding of adolescent menstrual health CONCLUSION In conclusion, this study identified age, protein and fiber intake, and depression as significant predictors of menstrual regularity among adolescents. Sufficient dietary intake of protein and fiber may help prevent irregular menstrual cycles, while a history of secondary amenorrhea and severe depression increases the likelihood of menstrual irregularities. By integrating these findings into the SDG framework, the study underscores the importance of localized health interventions in achieving global health equity. Meanwhile, his study highlights key adolescent health needs related to menstrual irregularities, contributing to SDG 3.7 on reproductive healthcare access. Improving menstrual health may also support SDG 4.1 and 4.5 by reducing school absenteeism and addressing gender disparities in education, and aligns with SDG 5.6, which promotes universal access to reproductive health. These findings emphasize the need for targeted, school-based nutrition and mental health interventions in urban Indonesian settings. Declarations Ethics approval and consent to participate: Before data collection, this study gained written informed consent from all participants, and subject participation was voluntary. The researcher asked each female high school student aged 16 and up who was willing to participate to sign an informed consent form. Moreover, the researcher also obtained parental consent before getting data from respondents under the age of 16. This study was guided by the ethical principles of the Declaration of Helsinki, which emphasizes the importance of protecting research subjects' rights, safety, and welfare. The University of Muhammadiyah Malang Research Ethics Committee authorized the study protocol (Ethical Certificate No. E.5.a/181/KEPK-UMM/X/2019) before its start. All research subjects were thoroughly informed about the study's objective, procedures, potential dangers, and benefits, and they were allowed to ask any concerns. Researchers also maintain participant confidentiality and privacy throughout and after the research procedure. Consent for publication: Not applicable Availability of data and materials: The data that support the findings of this study are available from the corresponding author upon reasonable request. Access to the data is restricted due to ethical considerations related to participant privacy. Competing interests: The authors declare no competing interests concerning this work. Funding: The authors declared that this research did not get grants from any public, commercial, or not-for-profit funding agency. However, the publishing charge of this study will be funded by the first author’s second affiliation. Authors’ contributions: Sendhi Tristanti Puspitasari, Anindya Hapsari, Tika Dwi Tama, and Olivia Andiana contributed to the study's conception and design. Sayyidah Hanifah, Fahni Haris and Muhammad Putra Ramadhan, processed and analyzed the data research. The manuscript was written by Sendhi Tristanti Puspitasari, Ferry Fadzlul Rahman, and Hung-En Liao, who revised it for important intellectual content. All authors approved the final version to be published. As a guarantor, Hung-En Liao is responsible for the overall content. Acknowledgements: This study could not have been accomplished without the assistance of the headmasters of four senior high schools in Malang, who permitted the researchers to collect respondents from their schools. The authors would like to thank the State University of Malang for allowing us to conduct this project among Malang's adolescents. We appreciate all project-minded people's support. Author information: Sendhi Tristanti Puspitasari : Email: [email protected] ; ORCID: https://orcid.org/0000-0003-1568-9384; 1. Department of Healthcare Administration, College of Medical and Health Science, Asia University, 500 Liufeng Road, Wufeng, Taichung City, Taiwan ROC. 2. Department of Medical Science, Faculty of Medicine, State University of Malang, Semarang Street No. 5, Malang City, Indonesia. - Ferry Fadzlul Rahman Email: [email protected] ; ORCID: https://orcid.org/0000-0002-6628-315X; Department of Public Health, Faculty of Public Health, Universitas Muhammadiyah Kalimantan Timur, Ir. H. Juanda Street No. 15, Samarinda City, Indonesia. Fahni Haris Email: [email protected] ; ORCID: https://orcid.org/0000-0002-2222-8554; School of Nursing, Faculty of Medicine and Health Sciences, Universitas Muhammadiyah Yogyakarta, Brawijaya Street Yogyakarta City, Indonesia. Anindya Hapsari : Email: [email protected] ; ORCID: https://orcid.org/0000-0003-2663-8232 Department of Medical Science, Faculty of Medicine, State University of Malang, Semarang Street No. 5, Malang City, Indonesia. Tika Dwi Tama : Email: [email protected] ; ORCID: https://orcid.org/0000-0003-4963-8243 Department of Public Health, Faculty of Sports Science, State University of Malang, Indonesia, Semarang Street No. 5, Malang City, Indonesia. Olivia Andiana : Email: [email protected] ; ORCID: https://orcid.org/0000-0002-1880-925X Department of Sports Science, Faculty of Sports Science, State University of Malang, Semarang Street No. 5, Malang City, Indonesia. Sayyidah Hannifah : Email: [email protected] ; ORCID: - Department of Public Health, Faculty of Sports Science, State University of Malang, Semarang Street No. 5, Malang City, Indonesia. Muhammad Putra Ramadhan : Email: [email protected] ; ORCID: https://orcid.org/0000-0003-1416-3954 Department of Nursing, Faculty of Medicine, State University of Malang, Semarang Street No. 5, Malang City, Indonesia. Hung-En Liao : Email: [email protected] ; ORCID: https://orcid.org/0000-0003-2840-6988 Department of Healthcare Administration, College of Medical and Health Science, Asia University, 500 Liufeng Road, Wufeng, Taichung City, Taiwan (Republic of China). References United Nation Population Fund (UNFPA) E and SA. The integration of menstrual health into sexual and reproductive health and rights policies and programmes. 2021;1–63. United Nations Development Programme. SDG Guidebook for Youth in Action. UNDP. 2022. Astuti EP, Noranita L. Prevalence of menstrual disorders based on body mass index (BMI) in seventh grade junior high school students. J Ilmu Kebidanan. 2016;58–64. Unuane D, Tournaye H, Velkeniers B, Poppe K. Endocrine disorders & female infertility. Best Pract Res Clin Endocrinol Metab. 2011;861–73. Rundell K, Panchal B. Being Reproductive. Prim Care Clin Off Pract. 2018;587–98. Macut D, Milutinovic DV, Markovic AR, Nestorov J, Macut JB, Stanojlovic O. A decade in female reproduction: an endocrine view of the past and into the future. Hormones. 2018;497–505. Nair M, Peate I, Sari YI, Damayanti R, Bariid B, Indri NP. Fundamentals of applied pathophysiology: an essential guide for nursing and health students. Jakarta: Bumi Aksara; 2015. Milanti I, Sulistiawati, Fransiska N, Nugroho H. The Relationship Between Stress and Menstrual Cycle Patterns in Undergraduate Students of the Nursing Science Study Program in Final Year. J Kebidanan Mutiara Mahakam. 2017;10–7. Kulsum U, Astuti D. The Menstrual Cycle and Nutritional Status. 1st Int Conf Sci Heal Econ Educ Technol (ICoSHEET). Semarang Atl Press. 2019;199–202. Guyton A, Hall J. Textbook Of Medical Physiology 12th Edition. In Philadelphia: Elsivier Saunders.; 2012. Kafeel H, Rukh R, Zubair A, Ghazala A, Muzaffar H, Raees H et al. Prevalance and Factors Associated With Functional Secondary Amenorrhea. Int J Pharm 2014;13–21. Oktavia F, Desmiwarti, Yaunin Y. Relationship between Anxiety and the Incidence of Secondary Amenorrhea in Medical Students of the Faculty of Medicine, Andalas University. J Kesehat Andalas. 2015;130–5. Pan D, Yan N, Pu L, He X, Wang H, Zhang X, et al. The association between urbanization and adolescent depression in China. PeerJ. 2024;12:1–15. Sabaei Y, Sabaei S, Khorshidi D, Ebrahimpour S, Rostami FF. The Association between Premenstrual Syndrome and Physical Activity and Aerobic Power in Female High School Students. Crescent J Med Biol Sci [Internet]. 2015;2(2):53–8. Tersedia pada:. http://www.cjmb.org . Aryani I, Rahma UP, Rokhayati E, Moelyo AG. Menstrual cycle patterns of Indonesian adolescents. Paediatr Indones. 2018;Paediatric:101–5. Pratami M, Herawati L, Annas JY. Menstrual Pattern Disorder Related to Physical Activity and Stress Psychic Soldiers Female Student of Indonesian Navy. Indian J Public Heal Res Dev. 2020;686–91. Spetz G. Nutritional Considerations for a Healthy Menstrual Cycle. Clevel Found Female Heal Aware; 2019. Briden L. Period Repair Manual: Natural Treatment for Better Hormones and Better Periods. In New York: Scribner; 2017. Situmorang H, Sutanto RL, Tjoa K, Rivaldo R, Adrian M. Prevalence and risk factors of primary dysmenorrhoea among medical students: a cross-sectional survey in Indonesia. BMJ Open. 2024;14(10):e086052. WHO. A healthy lifestyle - WHO recommendations [Internet]. WHO recommendations. 2010. Tersedia pada: https://www.who.int/europe/news-room/fact-sheets/item/a-healthy-lifestyle---who-recommendations Lavoie J, Douglas KS. The Perceived Stress Scale: Evaluating Configural, Metric, and Scalar Invariance across Mental Health Status and Gender. J Psychopathol Behav Assess. 2011;1–11. Ginting H, Näring G, Van Der Veld WM, Srisayekti W, Becker ES. Validating the Beck Depression Inventory-II in Indonesia’s general population and coronary heart disease patients. Int J Clin Heal Psychol [Internet]. 2013;13(3):235–42. http://dx.doi.org/10.1016/S1697-2600(13)70028-0 . Tersedia pada:. Amelia WR. The relationship between body mass index and other factors with body fat status in waiters at the nutrition service of the integrated inpatient unit of building A of RSUPN Dr. Cipto Mangunkusumo Hospital Jakarta. Jakarta Univ Indones; 2009. Cleland C, Ferguson S, Ellis G, Hunter RF. Validity of the International Physical Activity Questionnaire (IPAQ) for assessing moderate-to-vigorous physical activity and sedentary behaviour of older adults in the United Kingdom. BMC Med Res Methodol. 2018;1–12. Rigon F, Sanctis VD, Bernasconi S, Bianchin L, Bona G, Bozzola M et al. Menstrual pattern and menstrual disorders among adolescents: an update of the Italian data. Ital J Pediatr. 2012;1–8. Kavita S, Jasleen K. Exploring The Paradigm Shift from Equality to Dignity with Special Reference to Women’s Rights Related to Menstrual Hygiene in India and Europe. Underst Connect Sustain Dev Goals Educ Adm Theory Pract. 2024;6037–47. Yermachenko A, Dvornyk V. Nongenetic Determinants of Age at Menarche: A Systematic Review. Biomed Res Int. 2014;1–14. Sitoayu L, Pertiwi DA, Mulyani EY. Macronutrient adequacy, nutritional status, stress, and menstrual cycle in adolescents. J Gizi Klin Indones. 2017;121–8. Nuryanti HS, Sari DR, Susilowati Y, Faridah I. Relationship status with nutrition and psychological stress on order menstrual cycles for young women. Nurs Care Open Access J. 2019;180–3. Wahyuni Y, Dewi R. Menstrual Cycle Disorders in Relation to Nutrient Intake in Vegetarian Teenagers. Indones J Nutr. 2018;76–81. Ismail C, Al-Hourani H, Lightowler HJ, Aldhaheri AS, Henry CK. Energy and Nutrient Intakes during Different Phases of the Menstrual Cycle in Females in the United Arab Emirates. Ann Nutr Metab. 2009;124–8. Padda J, Khalid K, Hitawala G, Batra N, Pokhriyal S, Mohan A et al. Depression and Its Effect on the Menstrual Cycle. Cureus. 2021;1–10. Chauhan S, Kumar P, Patel R, Srivastava S, Simon RO. DJ, Association of lifestyle factors with menstrual problems and its treatment-seeking behavior among adolescent girls. Clin Epidemiol Glob Heal. 2021;1–6. UNESCO. Menstrual health and hygiene management: A module for teachers and educators. New Delhi. UNESCO New Delhi Multisectoral Reg Off [Internet]. 2023; Tersedia pada: https://healtheducationresources.unesco.org/library/documents/menstrual-health-and-hygiene-management-module-teachers-and-educators World Health Organization. Mental health of children and young people: Service guidance.Mental health of children and young people: Service guidance. Geneva [Internet]. 2024; Tersedia pada: https://www.who.int/publications/i/item/9789240100374 Additional Declarations No competing interests reported. Supplementary Files FFQQuestionnaire.docx questionnaireBDIII.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5538953","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":446161988,"identity":"60d2827c-572d-4865-8172-ca5d6c289702","order_by":0,"name":"Sendhi Tristanti Puspitasari","email":"","orcid":"","institution":"Asia University","correspondingAuthor":false,"prefix":"","firstName":"Sendhi","middleName":"Tristanti","lastName":"Puspitasari","suffix":""},{"id":446161989,"identity":"4103bde9-56e4-4276-a6d5-d633ef5ecdc9","order_by":1,"name":"Ferry Fadzlul Rahman","email":"","orcid":"","institution":"Universitas Muhammadiyah Kalimantan 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03:23:18","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5538953/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5538953/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":81200827,"identity":"ab781157-8d45-402f-b019-08888ce42a61","added_by":"auto","created_at":"2025-04-23 11:14:44","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":40288,"visible":true,"origin":"","legend":"\u003cp\u003eFlowchart of the Cluster Sampling Method Used in Selecting Female Adolescent Participants in Malang City\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-5538953/v1/b5592d70d19260d24d45cd5b.png"},{"id":96805470,"identity":"83c50ea8-ce46-4827-aae3-3e63828a5fd4","added_by":"auto","created_at":"2025-11-26 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11:14:45","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":33472,"visible":true,"origin":"","legend":"","description":"","filename":"questionnaireBDIII.docx","url":"https://assets-eu.researchsquare.com/files/rs-5538953/v1/f8d5aa08b95e2e236cd93687.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Understanding Menstrual Irregularities in Adolescents: Key Factors and Their Role in Achieving Sustainable Development Goals","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eA holistic approach to menstrual health and sexual reproductive health can give girls, and women the knowledge, skills, support, and resources they need to thrive. Menstrual health is essential to achieving a world where every pregnancy is wanted, every childbirth is safe, and every young person's potential is fulfilled. Moreover, the Sustainable Development Goals and United Nation Youth 2030 include supporting girls, and women to manage menstruation safely and with dignity (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). The reproductive health of adolescent girls is a source of world strength because the global youth population is expected to be 15% of the population by 2030, or 1.3\u0026nbsp;billion out of 8.5\u0026nbsp;billion. If global sustainable development is not accelerated, many young people will suffer from starvation, disease, dropping out of school, poverty, and air pollution (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMenstrual health is closely connected to achieving several Sustainable Development Goals (SDGs). SDG 3 emphasizes universal access to sexual and reproductive healthcare services, including education on menstrual health management. Furthermore, menstrual health directly impacts adolescents' school attendance and academic performance\u0026mdash;issues central to achieving SDG 4 (quality education). Adolescents experiencing menstrual irregularities may face increased school absenteeism, reduced academic engagement, and impaired performance, highlighting the critical need for effective menstrual health management. Additionally, ensuring menstrual health aligns closely with SDG 5, which aims for gender equality and empowerment of women and girls by addressing health-related barriers to their full participation in society (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDespite global awareness, Menstrual disorders, such as secondary amenorrhea and irregular menstrual cycles, can significantly impact the quality of life, daily activities, and academic performance of female adolescents (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). secondary amenorrhea due to its significant impact on adolescent reproductive health, potential long-term consequences, and its role as an indicator of underlying stress, dietary, or physical activity issues common in urban settings (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Secondary amenorrhea, affecting approximately 20% of women with ovulatory dysfunction, is an early indicator of reproductive health issues (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). It is defined as the absence of menstruation for three consecutive months in females aged 12 to 49 (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). Various factors, including pregnancy, significant weight changes, strenuous exercise, elevated prolactin levels, and stress, can lead to secondary amenorrhea (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). Untreated, it can result in infertility or difficulties in conception (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe prevalence of secondary amenorrhea varies globally. Previous studies have shown that only 10\u0026ndash;15% of women experience regular 28-day cycles, with menstrual durations of 3\u0026ndash;7 days (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). Irregular menstruation can also lead to secondary amenorrhea. Stress, dietary patterns, physical activity, body mass index (BMI), depression, and hormonal imbalances contribute to menstrual irregularities (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). In Pakistan, Kafael reported a secondary amenorrhea prevalence of 44.8% among students (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e), whereas a study in Indonesia found that 28.0% of 242 medical students experienced secondary amenorrhea (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eRecent evidence underscores the role of chronic psychosocial stress among urban adolescents, characterized by intense academic pressures, rapid urbanization, and socio-economic disparities ((\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e)). This stress-induced elevation of cortisol levels may disrupt the HPG axis, highlighting the importance of examining stress as a potential contributor to menstrual irregularities despite mixed empirical results. additionally, physical activity has emerged as a nuanced factor affecting menstrual regularity among urban adolescents. While moderate physical activity supports menstrual health by maintaining hormonal balance, extreme physical exertion or prolonged sedentary behavior can lead to significant menstrual disruptions, thus warranting detailed examination in adolescent populations ((\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e))\u003c/p\u003e \u003cp\u003eFactors contributing to menstrual irregularities may vary across countries. In a study of 200 Indonesian high school students, Aryani found that 24.5% had irregular cycles. However, this was not significantly influenced by BMI, age, age at menarche, nutritional status, physical activity, or fat intake (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). Pratami et al. discovered that 86.3% of female Indonesian Navy cadets had menstrual disorders, with 29.6% experiencing secondary amenorrhea. Heavy exercise (96.8%) and low-stress levels (76.8%) were also significant factors (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eNutritional intake plays a critical role in maintaining regular menstrual cycles. Diets rich in protein, plant-based fats, and high-fiber carbohydrates provide the body with essential nutrients for hormone production (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). However, vegetarian diets may affect protein intake, lacking essential amino acids and phytoestrogens, which could have anti-estrogenic effects (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDietary patterns, a key determinant of menstrual health, are deeply rooted in cultural and regional contexts. In Indonesia, a predominantly plant-based diet, featuring tofu and Tempe as protein staples, introduces unique nutritional factors that may influence hormonal regulation (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). This dietary context, combined with limited access to mental health resources and nutrition education, creates a distinct environment for menstrual health challenges (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). Malang City, a rapidly urbanizing region, exemplifies this intersection of traditional dietary habits and modern lifestyle pressures. Therefore, exploring dietary patterns specifically among adolescents in rapidly urbanizing regions like Malang City, where traditional plant-based dietary habits intersect with increasing consumption of processed foods is particularly important. Clarifying how these localized dietary factors, together with psychosocial and physical activity conditions, influence menstrual irregularities will help tailor region-specific interventions that align closely with the real-life context of Indonesian adolescents.\u003c/p\u003e \u003cp\u003eDespite growing attention to menstrual health among adolescents globally, the unique lifestyle and dietary patterns of the Indonesian population, which is also one of the world's developing countries, this study aims to determine the prevalence of menstrual irregularities among adolescents in Malang City and explore the relationships between these irregularities and associated factors, such as dietary intake, stress, and physical activity. This study addresses these gaps by concurrently investigating stress, depression, dietary intake, and physical activity as combined predictors of menstrual irregularities, providing essential insights for targeted local interventions aligned with Sustainable Development Goals (SDGs)\u003c/p\u003e"},{"header":"METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design, settings, and participants\u003c/h2\u003e \u003cp\u003eThis study employed a cross-sectional design, suitable for assessing the prevalence of menstrual irregularities and their associated factors among adolescents in Malang City, Indonesia. The Health Research Ethics Committee at the University of Muhammadiyah Malang approved the research (Certificate No.E.5.a/181/KEPK-UMM/X/2019), and informed consent was obtained from all participants. The study adhered to ethical standards, ensuring participant confidentiality and sensitivity in handling menstrual health data.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eSample size and sampling procedures\u003c/h3\u003e\n \u003cp\u003eFigure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003e defined cluster sampling was employed to ensure diverse representation from different sub-districts within Malang City, capturing a broad spectrum of socio-demographic factors. The sample size was calculated based on an assumed prevalence of menstrual irregularities among adolescents (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e), with a 95% confidence interval, resulting in a target sample of 529 respondents. After initial screening and data cleaning, completed questionnaires from 482 students were included for analysis.\u003c/p\u003e\n\u003ch3\u003eQuestionnaire Variables\u003c/h3\u003e\n\u003cp\u003eThe study utilized validated and reliable questionnaires to assess various variables, including stress levels, depression, nutrition frequency, physical activity, sociodemographic data, and self-reported menstrual characteristics. Psychological factors were measured using the Perceived Stress Scale (PSS) and Beck Depression Inventory \u0026ndash; II questionnaire (BDI-II), both of which are well-suited for adolescent populations.\u003c/p\u003e\n\u003ch3\u003eMenstrual health and cycle definition\u003c/h3\u003e\n\u003cp\u003eMenstrual health is a state of complete physical, mental, and social well-being and not merely the absence of disease or infirmity to the menstrual cycle, in which women, girls and all people who menstruate experience a positive and respectful environment, free from stigma and psychological distress, with the resources and support they need to care for their bodies confidently and make informed decisions about self-care throughout the life course; and the freedom to decide whether and how to participate in all spheres of life, including civil, cultural, economic, social, and political, free from menstrual-related exclusion, restriction, discrimination, coercion, and or violence (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMenstrual cycle regularity was classified based on the International Federation of Gynecology and Obstetrics (FIGO) standards (2018), where a regular cycle was defined as occurring every 24\u0026ndash;38 days without secondary amenorrhea in the preceding three months.\u003c/p\u003e\n\u003ch3\u003ePredictors\u003c/h3\u003e\n\u003cp\u003eBody Mass Index (BMI) was calculated based on self-reported height and weight data and classified into underweight (BMI\u0026thinsp;\u0026lt;\u0026thinsp;18.5), normal weight (BMI 18.5 to 24.5), and overweight (BMI\u0026thinsp;\u0026gt;\u0026thinsp;24.5) (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). Stress levels were assessed using the PSS, with respondents categorized into mild, moderate, and severe stress based on their scores. Depression was measured using the BDI, with scores categorized into mild (0\u0026ndash;19) and severe (\u0026gt;\u0026thinsp;20) depression. Nutritional intake was assessed using a modified Food Frequency Questionnaire (FFQ), and physical activity was evaluated using the International Physical Activity Survey (IPAQ).\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThe Perceived Stress Scale (PSS) is a seven-item psychological self-report test with multiple-choice answers. It was divided into three groups based on the PSS score: mild (\u003cspan additionalcitationids=\"CR2 CR3 CR4 CR5 CR6 CR7 CR8 CR9 CR10 CR11 CR12 CR13\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e), moderate (\u003cspan additionalcitationids=\"CR16 CR17 CR18 CR19 CR20 CR21 CR22 CR23 CR24 CR25\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e), and severe (more than 26) (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). Adapted from Ginting, 2013, the Beck Depression Inventory (BDI) questionnaire was used to determine depression levels (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). Researchers in this study re-categorized the outcomes into two groups: mild depression group (0\u0026ndash;19) and severe depression group (\u0026gt;\u0026thinsp;20). The Perceived Stress Scale (PSS) and Beck Depression Inventory (BDI) were selected for this study due to their widespread use in adolescent populations and their ability to capture the psychological dimensions relevant to menstrual health.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eThis survey used a modified FFQ (Food Frequency Qualitative) questionnaire validated for the Indonesian population. Food items were grouped into five categories: carbohydrates, fats, proteins, fiber-containing foods, and snacks. Consumption frequency was divided into two categories: \u0026ldquo;sufficient\u0026rdquo; if eaten 3\u0026ndash;4 times daily, and \u0026ldquo;less\u0026rdquo; if eaten ˂ 3 times daily. The frequency score was calculated by the total number of times each respondent consumed the food and then divided by the total number of respondents based on the original survey (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e).\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eShort-form questionnaires from the International Physical Activity Survey (IPAQ), revalidated by Amelia in 2009, Explicitly clarified and cited the validation of IPAQ short-form for Indonesian populations were used to determine the respondents\u0026rsquo; physical activity. Frequencies of heavy and moderate physical activity were measured. Three levels were defined for heavy physical activity: low (20 hours per week), middle (20\u0026ndash;89 hours per week), and high (\u0026gt;\u0026thinsp;90 hours per week), and moderate physical activity: low (less than 50 minutes per week), middle (between 50 and 70 minutes per week), and high (more than 70 minutes per week) (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eData analysis\u003c/h2\u003e \u003cp\u003eData were analyzed using SPSS version 25. Descriptive statistics were used to summarize categorical variables as frequencies and percentages, and continuous variables as means and standard deviations. Bivariate analyses (\u003cem\u003et-test\u003c/em\u003e and \u003cem\u003echi-square\u003c/em\u003e) were conducted to explore relationships between independent variables and menstrual irregularities, Cases with missing values on key variables were excluded using listwise deletion. Only respondents with complete data across all variables of interest were included in the final analysis (n\u0026thinsp;=\u0026thinsp;482). Effect sizes were reported using odds ratios (ORs) with 95% confidence intervals from logistic regression analyses to quantify the strength of association between predictors and menstrual irregularitie\u003cb\u003es\u003c/b\u003e. Logistic regression was used to identify significant predictors of menstrual cycle irregularity, with a significance threshold set at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05. A stepwise logistic regression analysis was performed using backward elimination based on a p-value threshold of 0.10 to retain meaningful predictors while improving model parsimony. Multi-collinearity was assessed using the Variance Inflation Factor (VIF), and all included variables had VIF values\u0026thinsp;\u0026lt;\u0026thinsp;2. Odds ratios (OR) with 95% confidence intervals (CI) were reported. Additionally, a ΔOR column was included to show the percentage change in OR values across model iterations\u003c/p\u003e \u003c/div\u003e"},{"header":"RESULTS","content":"\u003cp\u003e\u003cstrong\u003eSocio-demographic characteristic\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 482 respondents completed the questionnaires, among which 16.2% (n = 78) reported irregular menstrual cycles, while 83.8% (n = 404) had regular cycles. The ages of the respondents ranged from 14 to over 19 years (Mean \u0026plusmn; SD: 16.24 \u0026plusmn; 1.11). The majority of participants in the irregular menstrual cycle group were aged between 14 and 16 years (67.95%), whereas participants with regular menstrual cycles were significantly older (p = 0.044). The mean age of menarche for all respondents was 12.41 years.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1. The distribution of respondents by age, menarche age, menstrual cycle characteristics, and menstrual cycle\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"605\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" style=\"width: 227px;\"\u003e\n \u003cp\u003eMenstrual Cycle Characteristics\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" style=\"width: 227px;\"\u003e\n \u003cp\u003eMenstrual Cycle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" style=\"width: 76px;\"\u003e\n \u003cp\u003eOR (95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" style=\"width: 76px;\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 113px;\"\u003e\n \u003cp\u003eRegular\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 113px;\"\u003e\n \u003cp\u003eIrregular\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 227px;\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003cp\u003e14-16\u003c/p\u003e\n \u003cp\u003e17-19\u003c/p\u003e\n \u003cp\u003e\u0026gt;19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e213\u003c/p\u003e\n \u003cp\u003e190\u003c/p\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e52.7%\u003c/p\u003e\n \u003cp\u003e47%\u003c/p\u003e\n \u003cp\u003e0.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e53\u003c/p\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e68%\u003c/p\u003e\n \u003cp\u003e32%\u003c/p\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e0.044*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 227px;\"\u003e\n \u003cp\u003eMean \u0026plusmn; SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"6\" valign=\"top\" style=\"width: 378px;\"\u003e\n \u003cp\u003e16.24 \u0026plusmn; 1.117\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 227px;\"\u003e\n \u003cp\u003eMin \u0026ndash; Max\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"6\" valign=\"top\" style=\"width: 378px;\"\u003e\n \u003cp\u003e14 \u0026ndash; 20\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 227px;\"\u003e\n \u003cp\u003eAge of Menarche\u003c/p\u003e\n \u003cp\u003eMean \u0026plusmn; SD\u003c/p\u003e\n \u003cp\u003eMin \u0026ndash; Max\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"6\" valign=\"top\" style=\"width: 378px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e12.41 \u0026plusmn; 1.127\u003c/p\u003e\n \u003cp\u003e9-16\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 227px;\"\u003e\n \u003cp\u003eHistory of secondary amenorrhea\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e370\u003c/p\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e91.6%\u003c/p\u003e\n \u003cp\u003e8.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e51\u003c/p\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e65.4%\u003c/p\u003e\n \u003cp\u003e34.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e5.761\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003ep \u0026lt; 0.001 *\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 227px;\"\u003e\n \u003cp\u003eHistory of taking medicine\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e389\u003c/p\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e96.3%\u003c/p\u003e\n \u003cp\u003e3.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e75\u003c/p\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e96.2%\u003c/p\u003e\n \u003cp\u003e3.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e0.955\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 227px;\"\u003e\n \u003cp\u003eHistory of the family for secondary amenorrhea\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e402\u003c/p\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e99.5%\u003c/p\u003e\n \u003cp\u003e0.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e76\u003c/p\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e97.4%\u003c/p\u003e\n \u003cp\u003e2.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e0.125\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e*p \u0026lt; \u0026alpha;, \u0026alpha; = 0.05 with chi-square test\u003c/p\u003e\n\u003cp\u003eAdditionally, 91.6% of respondents with regular cycles and 65.4% with irregular cycles did not have a history of secondary amenorrhea. Similarly, 96.3% of respondents with regular cycles and 96.2% with irregular cycles reported no history of medication use.\u003c/p\u003e\n\u003cp\u003eA significant connection between secondary amenorrhea and the menstrual cycle (p = p \u0026lt; 0.001 , OR = 5.761) was found. This shows that people with a history of secondary amenorrhea are 5.761 times more likely to have irregular menstrual cycles. However, this statistical test indicated a lack of significance between medicine use (p = 0.955) and family history of secondary amenorrhea (p = 0.125) with menstruation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFactors associated with menstrual irregularity.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStress and Depression\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe results showed that 89.6% of respondents with regular cycles and 84.6% of those with irregular cycles experienced moderate stress. No significant relationship was found between stress and menstrual irregularities (p = 0.312).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2. The distribution of respondents by stress, depression, and menstrual cycle\u003c/strong\u003e\u003cstrong\u003eRisk Factor\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"619\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCategory\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 258px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMenstrual cycle\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOR (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIrregular (n, %)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRegular (n, %)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDepression\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003eSevere\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e32 (41%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e107 (28.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e1.931\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.009*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003eMild\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e46 (59%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e297 (71.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStress\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003eModerate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e66 (84.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e361 (89.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e0.655\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.312\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003eMild\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e12 (15.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e43 (10.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e*p \u0026lt; \u0026alpha;, \u0026alpha; = 0.05 with a chi-square test\u003c/p\u003e\n\u003cp\u003eHowever, depression was significantly associated with menstrual irregularity (p = 0.009). Respondents with severe depression were 1.931 times more likely to experience irregular menstrual cycles than those with mild depression (OR = 1.931).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3. The distribution of respondents by a sedentary lifestyle, physical activity, and menstrual cycle\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"623\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRisk Factor\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCategory\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 247px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMenstrual Cycle\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOR (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eIrregular (n, %)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eRegular (n, %)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHeavy Physical Activity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e22 (28.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e87 (21.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.431\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.254\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e56 (71.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e317 (78.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eModerate Physical Activity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e70 (88.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e346 (85.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.467\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.433\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8 (11.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e58 (14.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSedentary Lifestyle\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e49 (63.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e251 (63.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.030\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.908\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eEnough\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e29 (37.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e153 (37.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e*p \u0026lt; \u0026alpha;, \u0026alpha; = 0.05 with chi-square test\u003c/p\u003e\n\u003cp\u003eIn both the regular and irregular menstrual cycle groups, a high proportion of respondents engaged in moderate physical activity (78.5% and 71.8%, respectively). However, no significant relationship was observed between physical activity, sedentary lifestyle, and menstrual cycle irregularity (p = 0.908; p = 0.254; p = 0.433, respectively).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4. The distribution of respondents by BMI, nutritional intake, and menstrual cycle\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eRisk Factor\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCategory\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMenstrual cycle\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eOR (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eIrregular (n, %)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eRegular (n, %)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eProtein Intake\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLess\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e34 (43.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e98 (24.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.414\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ep \u0026lt; 0.001 *\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSufficient\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e44 (56.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e306 (75.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eFiber Intake\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLess\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e24 (30.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e78 (19.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.538\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.023*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSufficient\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e54 (69.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e326 (80.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eFat Intake\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSufficient\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e22 (28.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e97 (24%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.243\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.431\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLess\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e56 (71.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e307 (76%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCarbohydrate Intake\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLess\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e55 (70.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e276 (68.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.902\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.902\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSufficient\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e23 (29.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e128 (31.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSnack Intake\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSufficient\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e28 (35.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e138 (34.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.079\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.767\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLess\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e50 (64.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e266 (65.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eBMI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOverweight\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8 (10%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e45 (11.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.766\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNormal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e49 (63%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e236 (58.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eUnderweight\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e21 (27%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e123 (30.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e*p \u0026lt; \u0026alpha;, \u0026alpha; = 0.05 with chi-square test\u003c/p\u003e\n\u003cp\u003eRespondents with irregular menstrual cycles had the following nutritional patterns: 63% had normal BMI, 70.5% had insufficient carbohydrate intake, 56.4% had sufficient protein intake, and 69.2% had sufficient fiber intake. A significant relationship was found between menstrual cycle regularity and both protein (p = p \u0026lt; 0.001 ) and fiber intake (p = 0.023). \u003cstrong\u003eRespondents with sufficient protein intake had a 58.6% lower likelihood of experiencing irregular menstrual cycles compared to those with insufficient intake (OR = 0.414, 95% CI: 0.303\u0026ndash;0.849). Similarly, those with sufficient fiber intake had a 46.2% lower likelihood of irregular cycles (OR = 0.538, 95% CI: 0.318\u0026ndash;1.072\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 5. Bivariate Selection\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"601\" style=\"margin-right: calc(12%); width: 88%;\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 74.0793%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25.7791%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 74.0793%;\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003cp\u003eHistory of secondary amenorrhea\u003c/p\u003e\n \u003cp\u003eHistory of taking medicine\u003c/p\u003e\n \u003cp\u003eHistory of the family for secondary amenorrhea\u003c/p\u003e\n \u003cp\u003eStress\u003c/p\u003e\n \u003cp\u003eDepression\u003c/p\u003e\n \u003cp\u003eSedentary lifestyle\u003c/p\u003e\n \u003cp\u003eHeavy physical activity\u003c/p\u003e\n \u003cp\u003eModerate physical activity\u003c/p\u003e\n \u003cp\u003eBMI\u003c/p\u003e\n \u003cp\u003eCarbohydrate\u003c/p\u003e\n \u003cp\u003eProtein\u003c/p\u003e\n \u003cp\u003eFat\u003c/p\u003e\n \u003cp\u003eFiber\u003c/p\u003e\n \u003cp\u003eSnack\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25.7791%;\"\u003e\n \u003cp\u003e0.002*\u003c/p\u003e\n \u003cp\u003ep \u0026lt; 0.001 *\u003c/p\u003e\n \u003cp\u003e0.871\u003c/p\u003e\n \u003cp\u003e0.250\u003c/p\u003e\n \u003cp\u003e0.180\u003c/p\u003e\n \u003cp\u003e0.006*\u003c/p\u003e\n \u003cp\u003e0.249\u003c/p\u003e\n \u003cp\u003e0.271\u003c/p\u003e\n \u003cp\u003e0.213\u003c/p\u003e\n \u003cp\u003e0.775\u003c/p\u003e\n \u003cp\u003e0.866\u003c/p\u003e\n \u003cp\u003e0.007*\u003c/p\u003e\n \u003cp\u003e0.093\u003c/p\u003e\n \u003cp\u003e0.083\u003c/p\u003e\n \u003cp\u003e0.591\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e*p value \u0026lt; 0.05\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 6. Logistic regression modeling\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"645\" style=\"margin-right: calc(1%); width: 99%; margin-left: calc(0%);\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 31.816%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 7.3035%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eB\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 8.4198%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 10.0655%;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 10.4691%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 7.6284%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e∆ OR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 24.3605%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11.3372%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLower\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.9102%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eUpper\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.816%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003csup\u003est\u003c/sup\u003e Model\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003cp\u003eHistory of secondary amenorrhea\u003c/p\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003eStress\u003c/p\u003e\n \u003cp\u003eDepression\u003c/p\u003e\n \u003cp\u003eSedentary lifestyle\u003c/p\u003e\n \u003cp\u003eModerate physical activity\u003c/p\u003e\n \u003cp\u003eProtein\u003c/p\u003e\n \u003cp\u003eFat\u003c/p\u003e\n \u003cp\u003eFiber\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.3035%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e-0.853\u003c/p\u003e\n \u003cp\u003e1.687\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e-0.569\u003c/p\u003e\n \u003cp\u003e0.819\u003c/p\u003e\n \u003cp\u003e-0.289\u003c/p\u003e\n \u003cp\u003e0.609\u003c/p\u003e\n \u003cp\u003e-0.758\u003c/p\u003e\n \u003cp\u003e0.529\u003c/p\u003e\n \u003cp\u003e-0.574\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.4198%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.293\u003c/p\u003e\n \u003cp\u003e0.318\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.399\u003c/p\u003e\n \u003cp\u003e0.290\u003c/p\u003e\n \u003cp\u003e0.284\u003c/p\u003e\n \u003cp\u003e0.436\u003c/p\u003e\n \u003cp\u003e0.290\u003c/p\u003e\n \u003cp\u003e0.316\u003c/p\u003e\n \u003cp\u003e0.312\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.0655%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003cp\u003ep \u0026lt; 0.001\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.154\u003c/p\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003cp\u003e0.309\u003c/p\u003e\n \u003cp\u003e0.163\u003c/p\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003cp\u003e0.094\u003c/p\u003e\n \u003cp\u003e0.066\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.4691%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.426\u003c/p\u003e\n \u003cp\u003e5.406\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.566\u003c/p\u003e\n \u003cp\u003e2.268\u003c/p\u003e\n \u003cp\u003e0.749\u003c/p\u003e\n \u003cp\u003e1.838\u003c/p\u003e\n \u003cp\u003e0.469\u003c/p\u003e\n \u003cp\u003e1.698\u003c/p\u003e\n \u003cp\u003e0.563\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.6284%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.3372%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.241\u003c/p\u003e\n \u003cp\u003e2.903\u003c/p\u003e\n \u003cp\u003e0.415\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1.292\u003c/p\u003e\n \u003cp\u003e0.427\u003c/p\u003e\n \u003cp\u003e0.834\u003c/p\u003e\n \u003cp\u003e0.267\u003c/p\u003e\n \u003cp\u003e0.927\u003c/p\u003e\n \u003cp\u003e0.307\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.9102%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.760\u003c/p\u003e\n \u003cp\u003e10.046\u003c/p\u003e\n \u003cp\u003e1.343\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e4.072\u003c/p\u003e\n \u003cp\u003e1.295\u003c/p\u003e\n \u003cp\u003e2.200\u003c/p\u003e\n \u003cp\u003e0.832\u003c/p\u003e\n \u003cp\u003e3.191\u003c/p\u003e\n \u003cp\u003e1.039\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.816%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2\u003csup\u003end\u003c/sup\u003e Model\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003cp\u003eHistory of secondary amenorrhea\u003c/p\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003eStress\u003c/p\u003e\n \u003cp\u003eDepression\u003c/p\u003e\n \u003cp\u003eModerate physical activity\u003c/p\u003e\n \u003cp\u003eProtein\u003c/p\u003e\n \u003cp\u003eFat\u003c/p\u003e\n \u003cp\u003eFiber\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.3035%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e-0.821\u003c/p\u003e\n \u003cp\u003e1.673\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e-0.588\u003c/p\u003e\n \u003cp\u003e0.823\u003c/p\u003e\n \u003cp\u003e0.555\u003c/p\u003e\n \u003cp\u003e-0.732\u003c/p\u003e\n \u003cp\u003e0.501\u003c/p\u003e\n \u003cp\u003e-0.556\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.4198%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.292\u003c/p\u003e\n \u003cp\u003e0.317\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.399\u003c/p\u003e\n \u003cp\u003e0.290\u003c/p\u003e\n \u003cp\u003e0.434\u003c/p\u003e\n \u003cp\u003e0.289\u003c/p\u003e\n \u003cp\u003e0.314\u003c/p\u003e\n \u003cp\u003e0.311\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.0655%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003cp\u003ep \u0026lt; 0.001\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.140\u003c/p\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003cp\u003e0.200\u003c/p\u003e\n \u003cp\u003e0.011\u003c/p\u003e\n \u003cp\u003e0.111\u003c/p\u003e\n \u003cp\u003e0.074\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.4691%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.440\u003c/p\u003e\n \u003cp\u003e5.329\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.555\u003c/p\u003e\n \u003cp\u003e2.278\u003c/p\u003e\n \u003cp\u003e1.743\u003c/p\u003e\n \u003cp\u003e0.481\u003c/p\u003e\n \u003cp\u003e1.651\u003c/p\u003e\n \u003cp\u003e0.573\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.6284%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e3.28%\u003c/p\u003e\n \u003cp\u003e1.4%\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1.9%\u003c/p\u003e\n \u003cp\u003e0.43%\u003c/p\u003e\n \u003cp\u003e5.45%\u003c/p\u003e\n \u003cp\u003e2.55%\u003c/p\u003e\n \u003cp\u003e2.84%\u003c/p\u003e\n \u003cp\u003e1.77%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.3372%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.250\u003c/p\u003e\n \u003cp\u003e2.866\u003c/p\u003e\n \u003cp\u003e0.412\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1.297\u003c/p\u003e\n \u003cp\u003e0.811\u003c/p\u003e\n \u003cp\u003e0.276\u003c/p\u003e\n \u003cp\u003e0.903\u003c/p\u003e\n \u003cp\u003e0.313\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.9102%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e.783\u003c/p\u003e\n \u003cp\u003e9.882\u003c/p\u003e\n \u003cp\u003e1.339\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e4.091\u003c/p\u003e\n \u003cp\u003e2.129\u003c/p\u003e\n \u003cp\u003e.852\u003c/p\u003e\n \u003cp\u003e3.089\u003c/p\u003e\n \u003cp\u003e1.058\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.816%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3\u003csup\u003erd\u003c/sup\u003e Model\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003cp\u003eHistory of secondary amenorrhea\u003c/p\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003eStress\u003c/p\u003e\n \u003cp\u003eDepression\u003c/p\u003e\n \u003cp\u003eProtein\u003c/p\u003e\n \u003cp\u003eFat\u003c/p\u003e\n \u003cp\u003eFiber\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.3035%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e-0.800\u003c/p\u003e\n \u003cp\u003e1.691\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e-0.547\u003c/p\u003e\n \u003cp\u003e0.823\u003c/p\u003e\n \u003cp\u003e-0.703\u003c/p\u003e\n \u003cp\u003e0.479\u003c/p\u003e\n \u003cp\u003e-0.538\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.4198%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.291\u003c/p\u003e\n \u003cp\u003e0.316\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.398\u003c/p\u003e\n \u003cp\u003e0.289\u003c/p\u003e\n \u003cp\u003e0.287\u003c/p\u003e\n \u003cp\u003e0.314\u003c/p\u003e\n \u003cp\u003e0.310\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.0655%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003cp\u003ep \u0026lt; 0.001\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.170\u003c/p\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003cp\u003e0.014\u003c/p\u003e\n \u003cp\u003e0.127\u003c/p\u003e\n \u003cp\u003e0.083\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.4691%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.449\u003c/p\u003e\n \u003cp\u003e5.424\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.579\u003c/p\u003e\n \u003cp\u003e2.277\u003c/p\u003e\n \u003cp\u003e0.495\u003c/p\u003e\n \u003cp\u003e1.615\u003c/p\u003e\n \u003cp\u003e0.584\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.6284%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.02%\u003c/p\u003e\n \u003cp\u003e1.7%\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e4.32%\u003c/p\u003e\n \u003cp\u003e0.04%\u003c/p\u003e\n \u003cp\u003e2.91%\u003c/p\u003e\n \u003cp\u003e2.23%\u003c/p\u003e\n \u003cp\u003e1.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.3372%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.256\u003c/p\u003e\n \u003cp\u003e2.909\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.423\u003c/p\u003e\n \u003cp\u003e1.290\u003c/p\u003e\n \u003cp\u003e0.282\u003c/p\u003e\n \u003cp\u003e0.883\u003c/p\u003e\n \u003cp\u003e0.318\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.9102%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.799\u003c/p\u003e\n \u003cp\u003e10.009\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1.362\u003c/p\u003e\n \u003cp\u003e4.058\u003c/p\u003e\n \u003cp\u003e0.868\u003c/p\u003e\n \u003cp\u003e3.014\u003c/p\u003e\n \u003cp\u003e1.072\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.816%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e4\u003csup\u003eth\u003c/sup\u003e Model\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003cp\u003eHistory of secondary amenorrhea\u003c/p\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003eDepression\u003c/p\u003e\n \u003cp\u003eProtein\u003c/p\u003e\n \u003cp\u003eFat\u003c/p\u003e\n \u003cp\u003eFiber\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.3035%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e-0.811\u003c/p\u003e\n \u003cp\u003e1.682\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.765\u003c/p\u003e\n \u003cp\u003e-0.716\u003c/p\u003e\n \u003cp\u003e0.511\u003c/p\u003e\n \u003cp\u003e-0.519\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.4198%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.290\u003c/p\u003e\n \u003cp\u003e0.314\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.283\u003c/p\u003e\n \u003cp\u003e0.285\u003c/p\u003e\n \u003cp\u003e0.311\u003c/p\u003e\n \u003cp\u003e0.309\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.0655%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003cp\u003ep \u0026lt; 0.001\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003cp\u003e0.012\u003c/p\u003e\n \u003cp\u003e0.101\u003c/p\u003e\n \u003cp\u003e0.093\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.4691%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.444\u003c/p\u003e\n \u003cp\u003e5.374\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2.149\u003c/p\u003e\n \u003cp\u003e0.489\u003c/p\u003e\n \u003cp\u003e1.667\u003c/p\u003e\n \u003cp\u003e0.595\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.6284%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1.12%\u003c/p\u003e\n \u003cp\u003e0.93%\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e5.95%\u003c/p\u003e\n \u003cp\u003e2.04%\u003c/p\u003e\n \u003cp\u003e3.21%\u003c/p\u003e\n \u003cp\u003e1.88%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.3372%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.252\u003c/p\u003e\n \u003cp\u003e2.903\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1.233\u003c/p\u003e\n \u003cp\u003e0.279\u003c/p\u003e\n \u003cp\u003e0.905\u003c/p\u003e\n \u003cp\u003e0.325\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.9102%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.785\u003c/p\u003e\n \u003cp\u003e9.948\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e3.744\u003c/p\u003e\n \u003cp\u003e0.855\u003c/p\u003e\n \u003cp\u003e3.070\u003c/p\u003e\n \u003cp\u003e1.091\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.816%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e5\u003csup\u003eth\u003c/sup\u003e Model\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003cp\u003eHistory of secondary amenorrhea\u003c/p\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003eDepression\u003c/p\u003e\n \u003cp\u003eProtein\u003c/p\u003e\n \u003cp\u003eFiber\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.3035%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e-0.772\u003c/p\u003e\n \u003cp\u003e1.701\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.743\u003c/p\u003e\n \u003cp\u003e-0.644\u003c/p\u003e\n \u003cp\u003e-0.472\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.4198%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.288\u003c/p\u003e\n \u003cp\u003e0.312\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.281\u003c/p\u003e\n \u003cp\u003e0.280\u003c/p\u003e\n \u003cp\u003e0.305\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.0655%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003cp\u003ep \u0026lt; 0.001\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.008\u003c/p\u003e\n \u003cp\u003e0.021\u003c/p\u003e\n \u003cp\u003e0.122\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.4691%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.462\u003c/p\u003e\n \u003cp\u003e5.477\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2.103\u003c/p\u003e\n \u003cp\u003e0.525\u003c/p\u003e\n \u003cp\u003e0.624\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.6284%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e4.0%\u003c/p\u003e\n \u003cp\u003e1.9%\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2.18%\u003c/p\u003e\n \u003cp\u003e7.36%\u003c/p\u003e\n \u003cp\u003e4.86%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.3372%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.263\u003c/p\u003e\n \u003cp\u003e2.973\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1.212\u003c/p\u003e\n \u003cp\u003e0.303\u003c/p\u003e\n \u003cp\u003e0.343\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.9102%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.813\u003c/p\u003e\n \u003cp\u003e10.091\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e3.650\u003c/p\u003e\n \u003cp\u003e0.908\u003c/p\u003e\n \u003cp\u003e1.135\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 31.816%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e6\u003csup\u003eth\u003c/sup\u003e Model\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003cp\u003eHistory of secondary amenorrhea\u003c/p\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003eDepression\u003c/p\u003e\n \u003cp\u003eProtein\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.3035%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e-0.742\u003c/p\u003e\n \u003cp\u003e1.706\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.793\u003c/p\u003e\n \u003cp\u003e-0.704\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.4198%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.286\u003c/p\u003e\n \u003cp\u003e0.310\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.278\u003c/p\u003e\n \u003cp\u003e0.276\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.0655%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.010\u003c/p\u003e\n \u003cp\u003ep \u0026lt; 0.001\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003cp\u003e0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.4691%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.476\u003c/p\u003e\n \u003cp\u003e5.509\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2.209\u003c/p\u003e\n \u003cp\u003e0.495\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.6284%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1.08%\u003c/p\u003e\n \u003cp\u003e0.58%\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e5.04%\u003c/p\u003e\n \u003cp\u003e6.06%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.3372%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e.271\u003c/p\u003e\n \u003cp\u003e3.001\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1.280\u003c/p\u003e\n \u003cp\u003e.288\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.9102%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.835\u003c/p\u003e\n \u003cp\u003e10.114\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e3.813\u003c/p\u003e\n \u003cp\u003e0.849\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eLogistic regression analysis identified significant predictors of menstrual cycle irregularity. The final model included age, history of secondary amenorrhea, depression, and protein intake. A history of secondary amenorrhea was the strongest predictor of menstrual irregularities, with an odds ratio (OR) of 5.509 and a 95% confidence interval (CI) of 2.973\u0026ndash;10.091, indicating a significantly higher risk among those with a history of amenorrhea. Other significant factors included depression and protein intake.\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThis study aimed to examine the prevalence and contributing factors of menstrual irregularities among adolescents, with a focus on sociodemographic, dietary, and psychological factors. Our findings add to the growing body of literature on adolescent menstrual health, highlighting the critical roles of age, nutrition, and mental health in maintaining regular menstrual cycles. Improving adolescent menstrual health may contribute to better outcomes in well-being, education continuity, and gender equity, especially when supported by broader health and social interventions.\u003c/p\u003e \u003cp\u003eThe results indicated that age and dietary intake were significant factors in menstrual regularity. Previous research has shown that menarche is influenced by body weight, protein intake, family stress, and activity levels (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). The age of menarche is a significant factor in gaining well-being as a whole (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). Furthermore, early menarche correlates with early pregnancy and certain sexually transmitted infections (STIs) in low- and middle-income countries (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). While non-genetic factors such as premature birth can also delay sexual maturity (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e), our study emphasized the importance of nutrition and mental health in maintaining menstrual regularity in adolescence.\u003c/p\u003e \u003cp\u003eMost of the participants had normal BMI, and no significant association was found between BMI and menstrual regularity, which aligns with Kulsum's findings (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). However, this contrasts with studies by Sitoayu and Nuryanti, which identified a relationship between BMI and menstrual irregularities (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). These mixed results suggest that the relationship between BMI and menstrual health may be more complex, potentially influenced by other lifestyle factors.\u003c/p\u003e \u003cp\u003eDietary intake, specifically protein and fiber, was strongly associated with menstrual regularity in this study. Sufficient intake of these nutrients was linked to a lower likelihood of experiencing irregular cycles, supporting previous research on the role of nutrition in hormonal regulation (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). The participants\u0026rsquo; diets, rich in tofu, Tempe, and other protein sources, were in line with studies on vegetarian diets, which also found associations between nutrient intake and menstrual regularity (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). Protein, as a critical building block for cellular function, plays an essential role in prolonging the follicular phase, thus contributing to regular menstrual cycles (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eInterestingly, no significant associations were found between menstrual irregularities and stress, sedentary lifestyle, or BMI in this study. Depression can lead to hormonal imbalances by affecting the HPG axis, causing elevated cortisol levels that disrupt gonadotropin-releasing hormone (GnRH) production (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e). This finding underscores the importance of addressing mental health in adolescents, as untreated depression can have broader implications for reproductive health (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eNo significant relationship was found between physical activity and menstrual irregularities. This result is consistent with studies that did not observe significant differences in menstrual patterns based on general physical activity levels (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e). However, regular physical activity is known to contribute to overall health, including maintaining a healthy weight and improving insulin sensitivity, both of which are important for menstrual regulation.\u003c/p\u003e \u003cp\u003eWhile some irregular menstrual cycles may reflect normal physiological variation during adolescence, persistent irregularities can indicate underlying hormonal or health issues that may affect future reproductive health. When left unaddressed, menstrual health challenges may contribute to school absenteeism and reinforce social stigma, which in turn can limit educational opportunities and perpetuate gender-related disparities in adolescent health outcomes.\u003c/p\u003e \u003cp\u003eThe findings of this study highlight the role of traditional dietary patterns in influencing menstrual health among Indonesian adolescents. Tofu and Tempe, key components of the Indonesian diet, are rich in phytoestrogens, which can mimic estrogen in the body and potentially stabilize hormonal fluctuations (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). While similar effects of plant-based diets have been observed globally, their impact may be more pronounced in Indonesia due to the high prevalence of these foods in daily meals (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFurthermore, the socio-economic landscape of Malang City, characterized by urbanization and limited access to healthcare services, adds a layer of complexity. Adolescents with irregular menstrual cycles often experience compounded barriers, including stigma surrounding menstruation, lack of nutritional guidance, and inadequate mental health support (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). To address these challenges, culturally tailored interventions should include school-based nutrition programs emphasizing local foods, workshops for teachers to support menstrual health education, and accessible mental health services to reduce stigma and provide counseling for adolescents (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThis study has several limitations. First, the cross-sectional design prevents causal inferences between risk factors and menstrual irregularities. Second, self-reported data on menstruation, BMI, and lifestyle behaviors may be subject to recall and reporting bias. Third, potential confounding factors such as sleep quality, socioeconomic status, and hormonal contraceptive use were not measured.\u003c/p\u003e \u003cp\u003e By focusing on Indonesia's unique dietary and socio-cultural environment, this study contributes a regional perspective to the global discourse on adolescent menstrual health. These findings underscore the importance and diversity of integrating local context into global health strategies, ensuring that interventions are both effective and culturally appropriate.\u003c/p\u003e \u003cp\u003eThe study has significant drawbacks. The sample was limited to four senior high schools in Malang City using cluster sampling procedures, which may have underrepresented the diversity of Indonesian teenagers. Furthermore, using self-reported data on menstrual features and lifestyle factors increases the risk of memory bias or mistakes. Despite these restrictions, the researcher believes that by focusing menstrual health management in public health policies, educational programs, and economic strategies, we can ensure that everyone who menstruates can do so with dignity and without being limited in their potential. The teenagers will then have a brighter future based on human well-being, education, and gender equality (SDGs 3, 4, and 5) To validate these findings, future studies should use a larger sample size and objective indicators of menstrual health. Finally, by promoting menstrual health and equity in access to care, the study supports broader gender empowerment objectives. Although indirect, these pathways reflect how evidence-based, localized interventions can advance global health and development goals. Future research should use longitudinal designs and objective measures (e.g., stress biomarkers, activity trackers) to clarify causal links. Including factors like sleep, school stress, and healthcare access may also provide a more complete understanding of adolescent menstrual health\u003c/p\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eIn conclusion, this study identified age, protein and fiber intake, and depression as significant predictors of menstrual regularity among adolescents. Sufficient dietary intake of protein and fiber may help prevent irregular menstrual cycles, while a history of secondary amenorrhea and severe depression increases the likelihood of menstrual irregularities. By integrating these findings into the SDG framework, the study underscores the importance of localized health interventions in achieving global health equity. Meanwhile, his study highlights key adolescent health needs related to menstrual irregularities, contributing to SDG 3.7 on reproductive healthcare access. Improving menstrual health may also support SDG 4.1 and 4.5 by reducing school absenteeism and addressing gender disparities in education, and aligns with SDG 5.6, which promotes universal access to reproductive health. These findings emphasize the need for targeted, school-based nutrition and mental health interventions in urban Indonesian settings.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate:\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eBefore data collection, this study gained written informed consent from all participants, and subject participation was voluntary. The researcher asked each female high school student aged 16 and up who was willing to participate to sign an informed consent form. Moreover, the researcher also obtained parental consent before getting data from respondents under the age of 16. This study was guided by the ethical principles of the Declaration of Helsinki, which emphasizes the importance of protecting research subjects\u0026apos; rights, safety, and welfare.\u003c/p\u003e\n\u003cp\u003eThe University of Muhammadiyah Malang Research Ethics Committee authorized the study protocol (Ethical Certificate No. E.5.a/181/KEPK-UMM/X/2019) before its start. All research subjects were thoroughly informed about the study\u0026apos;s objective, procedures, potential dangers, and benefits, and they were allowed to ask any concerns. Researchers also maintain participant confidentiality and privacy throughout and after the research procedure.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u0026nbsp;\u003c/strong\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials:\u0026nbsp;\u003c/strong\u003eThe data that support the findings of this study are available from the corresponding author upon reasonable request. Access to the data is restricted due to ethical considerations related to participant privacy.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests:\u003c/strong\u003e The authors declare no competing interests concerning this work.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e The authors declared that this research did not get grants from any public, commercial, or not-for-profit funding agency. However, the publishing charge of this study will be funded by the first author\u0026rsquo;s second affiliation.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions:\u003c/strong\u003e\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003eSendhi Tristanti Puspitasari, Anindya Hapsari, Tika Dwi Tama, and Olivia Andiana contributed to the study\u0026apos;s conception and design.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eSayyidah Hanifah, Fahni Haris and Muhammad Putra Ramadhan, processed and analyzed the data research.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eThe manuscript was written by Sendhi Tristanti Puspitasari, Ferry Fadzlul Rahman, and Hung-En Liao, who revised it for important intellectual content.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eAll authors approved the final version to be published.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eAs a guarantor, Hung-En Liao is responsible for the overall content.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study could not have been accomplished without the assistance of the headmasters of four senior high schools in Malang, who permitted the researchers to collect respondents from their schools. The authors would like to thank the State University of Malang for allowing us to conduct this project among Malang\u0026apos;s adolescents. We appreciate all project-minded people\u0026apos;s support.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor information:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003e\u003cstrong\u003eSendhi Tristanti Puspitasari\u003c/strong\u003e:\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eEmail: [email protected]; ORCID: https://orcid.org/0000-0003-1568-9384;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e1. Department of Healthcare Administration, College of Medical and Health Science, Asia University, 500 Liufeng Road, Wufeng, Taichung City, Taiwan ROC.\u003c/p\u003e\n\u003cp\u003e2. Department of Medical Science, Faculty of Medicine, State University of Malang, Semarang Street No. 5, Malang City, Indonesia.\u003c/p\u003e\n\u003cp\u003e- \u003cstrong\u003eFerry Fadzlul Rahman\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEmail: [email protected]; ORCID: https://orcid.org/0000-0002-6628-315X; Department of Public Health, Faculty of Public Health, Universitas Muhammadiyah Kalimantan Timur, Ir. H. Juanda Street No. 15, Samarinda City, Indonesia.\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003e\u003cstrong\u003eFahni Haris\u003c/strong\u003e\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eEmail: [email protected]; ORCID: https://orcid.org/0000-0002-2222-8554; School of Nursing, Faculty of Medicine and Health Sciences, Universitas Muhammadiyah Yogyakarta, Brawijaya Street Yogyakarta City, Indonesia.\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003e\u003cstrong\u003eAnindya Hapsari\u003c/strong\u003e:\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eEmail: [email protected] ; ORCID: https://orcid.org/0000-0003-2663-8232 \u0026nbsp;Department of Medical Science, Faculty of Medicine, State University of Malang, Semarang Street No. 5, Malang City, Indonesia.\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003e\u003cstrong\u003eTika Dwi Tama\u003c/strong\u003e:\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eEmail: [email protected] ; ORCID: https://orcid.org/0000-0003-4963-8243\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDepartment of Public Health, Faculty of Sports Science, State University of Malang, Indonesia, Semarang Street No. 5, Malang City, Indonesia.\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003e\u003cstrong\u003eOlivia Andiana\u003c/strong\u003e:\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eEmail: [email protected] ; ORCID: https://orcid.org/0000-0002-1880-925X \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDepartment of Sports Science, Faculty of Sports Science, State University of Malang, Semarang Street No. 5, Malang City, Indonesia.\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003e\u003cstrong\u003eSayyidah Hannifah\u003c/strong\u003e:\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eEmail: [email protected] ; ORCID: -\u003c/p\u003e\n\u003cp\u003eDepartment of Public Health, Faculty of Sports Science, State University of Malang, Semarang Street No. 5, Malang City, Indonesia.\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003e\u003cstrong\u003eMuhammad Putra Ramadhan\u003c/strong\u003e:\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eEmail: [email protected] ; ORCID: \u0026nbsp;https://orcid.org/0000-0003-1416-3954 \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDepartment of Nursing, Faculty of Medicine, State University of Malang, Semarang Street No. 5, Malang City, Indonesia.\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003e\u003cstrong\u003eHung-En Liao\u003c/strong\u003e:\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eEmail: [email protected] ; ORCID: https://orcid.org/0000-0003-2840-6988\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDepartment of Healthcare Administration, College of Medical and Health Science, Asia University, 500 Liufeng Road, Wufeng, Taichung City, Taiwan (Republic of China).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eUnited Nation Population Fund (UNFPA) E and SA. 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Geneva [Internet]. 2024; Tersedia pada: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.who.int/publications/i/item/9789240100374\u003c/span\u003e\u003cspan address=\"https://www.who.int/publications/i/item/9789240100374\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"menstrual health, menstrual irregularities, sustainable development goal, adolescents, dietary patterns, psycho-social issues","lastPublishedDoi":"10.21203/rs.3.rs-5538953/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5538953/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eMenstrual health issues such as irregular menstruation and secondary amenorrhea can have a substantial impact on adolescent well-being. Since girls' reproductive health is crucial to global strength, the Sustainable Development Goals and United Nation Youth 2030 prioritize safe and dignified menstruation management. Despite the widespread recognition of numerous factors contributing to the risk of menstrual irregularities, this study investigated prevalence of menstrual irregularities among adolescents in Malang City, Indonesia, and to determine whether stress, depression, dietary intake, and physical activity are significant predictors of these irregularities.\u003c/p\u003e\u003ch2\u003eMethod\u003c/h2\u003e \u003cp\u003eA cross-sectional study was conducted using cluster sampling and questionnaires to collect data from 482 adolescents across five sub-districts in Malang City. Bivariate analyses, t-tests, chi-square tests, and logistic regression were performed using SPSS to identify factors associated with menstrual irregularities.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eMenstrual irregularities were reported by 16% of respondents. Adolescents with regular cycles were significantly older than those with irregular cycles (p\u0026thinsp;=\u0026thinsp;0.044, Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD: 16.24\u0026thinsp;\u0026plusmn;\u0026thinsp;1.11). Secondary amenorrhea occurred in 8.4% of respondents with regular cycles (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001 ). Severe depression was present in 41% of those with irregular cycles compared to 28.3% with regular cycles (p\u0026thinsp;=\u0026thinsp;0.004). A history of secondary amenorrhea was the strongest predictor of irregular cycles (OR\u0026thinsp;=\u0026thinsp;5.509), with age and protein intake also contributing.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eIn conclusion, age, protein intake, and depression significantly predict menstrual irregularities among adolescents in Malang City, Indonesia. Targeted interventions focusing on dietary education and mental health support could improve adolescent menstrual health and overall well-being. Future research should evaluate the effectiveness of these interventions. These findings show that adolescents need tailored dietary and mental health interventions to improve menstrual health and sustained growth.\u003c/p\u003e","manuscriptTitle":"Understanding Menstrual Irregularities in Adolescents: Key Factors and Their Role in Achieving Sustainable Development Goals","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-23 11:14:39","doi":"10.21203/rs.3.rs-5538953/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"5c0ec975-c6e8-425f-97ed-a36a04e26a5c","owner":[],"postedDate":"April 23rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-11-26T09:09:18+00:00","versionOfRecord":[],"versionCreatedAt":"2025-04-23 11:14:39","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5538953","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5538953","identity":"rs-5538953","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}