{"paper_id":"49595404-0dff-4957-8179-c2be8a64939b","body_text":"RESEARCH Open Access\nMiddle East Fertility\nSociety Journal\n© The Author(s) 2025. Open Access  This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, \nsharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and \nthe source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this \narticle are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included \nin the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will \nneed to obtain permission directly from the copyright holder. To view a copy of this licence, visit  h t t p  : / /  c r e a  t i  v e c  o m m  o n s .  o r  g / l i c e n s e s / b y / 4 . 0 /.\nBudihastuti et al. Middle East Fertility Society Journal           (2025) 30:65 \nhttps://doi.org/10.1186/s43043-025-00285-y\n*Correspondence:\nUki Retno Budihastuti\nukiretno@staff.uns.ac.id\n1Department of Obstetrics and Gynecology, Faculty of Medicine, \nUniversitas Sebelas Maret / Dr. Moewardi General Hospital, Ir. Sutami 36 A, \nKentingan, Surakarta, Jawa Tengah 57126, Indonesia\n2Department of Obstetrics and Gynecology, Faculty of Medicine, \nUniversitas Sebelas Maret / UNS Hospital, Ahmad Yani No. 200, \nMakamhaji, Kartasura, Sukoharjo, Jawa Tengah 57161, Indonesia\nAbstract\nBackground Dysmenorrhea or menstrual pain is a menstrual symptom that often occurs in almost all women of \nreproductive age, especially in adolescents. Dysmenorrhea itself is the most commonly complained-of symptom of \nendometriosis in adolescents. There are many factors that influence the incidence of adolescent dysmenorrhea. This \nstudy aimed to analyze factors predisposing adolescents to dysmenorrhea.\nMethods This cross-sectional study involved 211 first-grade students at Sekolah Menengah Atas Negeri (SMA N) 1 \nSurakarta, selected through total sampling based on inclusion and exclusion criteria. Dysmenorrhea incidence was \nthe dependent variable, with independent variables including menarche age, body mass index (BMI), menstrual \nregularity, menstrual cycle length, menstrual duration, family history of dysmenorrhea, breastfeeding history, and \ncigarette exposure. Data were analyzed with SPSS version 25.0, using Chi-Square for bivariate and logistic regression \nfor multivariate analysis.\nResult The prevalence of dysmenorrhea among adolescents was 89.1%. A significant association was found between \na family history of dysmenorrhea and dysmenorrhea incidence in adolescents (OR = 5.26; 95% CI = 1.92–14.45; \np = 0.001). Prolonged menstrual cycles were also significantly associated with dysmenorrhea (OR = 3.15; 95% CI = 1.13–\n8.80; p = 0.029).\nConclusion Family history of dysmenorrhea and prolonged menstrual cycles significantly increase the likelihood of \ndysmenorrhea in adolescents. These factors should be considered in managing adolescent dysmenorrhea, which can \nimpact daily activities and quality of life.\nKeywords Adolescent, Dysmenorrhea, Predisposition factor, Prevalence, Symptom\nPredisposing factors for adolescent \ndysmenorrhea in public high school students \nin Surakarta, Central Java, Indonesia\nUki Retno Budihastuti1*, Abdurahman Laqif1, Eriana Melinawati1, Darto1, Asih Anggraeni2, Agung Sari Wijayanti1 and \nAtthahira Amalia Hafiizha1\n\nPage 2 of 8\nBudihastuti et al. Middle East Fertility Society Journal            (2025) 30:65 \nIntroduction\nDysmenorrhea or menstrual pain is a menstrual symp -\ntom that affects the majority of women of reproductive \nage, particularly adolescents [ 1]. Among adolescents, \ndysmenorrhea significantly interferes with daily activi -\nties, including school attendance and academic perfor -\nmance. It is a leading cause of short-term absenteeism \nand decreased classroom participation, which collec -\ntively reduce effective learning outcomes such as concen-\ntration, comprehension, and memory retention during \nlessons [ 2, 3]. Dysmenorrhea is characterized by recur -\nrent cramping pain in the lower abdomen that occurs \nbefore or during menstruation and may be accompanied \nby nausea, fatigue, headache, and mood changes [ 4]. It is \ngenerally classified into two types, primary and second -\nary dysmenorrhea. Primary dysmenorrhea occurs when \nthere is menstrual pain without any abnormalities in the \npelvis. Meanwhile, secondary dysmenorrhea leads to \nmenstrual pain with the presence of pelvic abnormalities \nor other known medical conditions [5].\nAccording to the World Health Organization (WHO), \nadolescents are in the second phase of life and includes \nindiciduals aged 10–19 years [ 6]. The global prevalence \nof dysmenorrhoea is estimated to range between 43% \nand 93% among women of reproductive age [ 7]. A meta-\nanalysis involving over 20,000 young women from 38 \ncountries reported an average prevalence of 71.1%, with \nparticularly high rates among adolescents and university \nstudents [ 4]. Several risk factors have been identified, \nincluding early menarche, prolonged menstrual dura -\ntion, heavy flow, family history, smoking, lack of physical \nactivity, stress, and low body mass index (BMI) [ 8, 9]. In \naddition, psychosocial and environmental determinants \nsuch as job-related stress, limited menstrual education, \nand sociocultural stigma also contribute to the wide vari -\nation in prevalence and severity of dysmenorrhea across \npopulations [10].\nDifferences in the causes and associated factors of \ndysmenorrhea are evident across countries and demo -\ngraphic groups. Studies among working women in Egypt \nrevealed strong associations with workplace stress, early \nmenarche, and family history, whereas research among \nadolescents in China found that poor stress-coping abil -\nity significantly increased the likelihood of dysmenorrhea \n[8, 11]. In contrast, studies from Pakistan and Saudi Ara -\nbia demonstrated that BMI and lifestyle factors were the \nmost significant predictors among medical students [ 7, \n9].\nIn Indonesia, dysmenorrhea remains a significant \nreproductive health concern among young women. \nResearch conducted among medical students and adoles-\ncents in Central Java and Surakarta reported prevalence \nrates ranging from 79% to 91%, with significant associa -\ntions found for family history, BMI, and menstrual cycle \nlength [7, 12]. Although the prevalence of dysmenorrhea \nin adolescents is relatively high, there are still many ado -\nlescents who do not receive professional treatment [13].\nApart from that, something that needs to be evaluated \nin adolescents with dysmenorrhoea is identifying factors \nthat increase the risk of dysmenorrhoea. Previous studies \nhave identified several factors that influence the occur -\nrence of dysmenorrhoea, both primary and secondary, \nsuch as early age at menarche, excessive menstrual blood \nvolume, family history, smoking, alcohol consumption, \nobesity, and other social factors [ 13, 14]. However, con -\nflicting study results often emerge between studies.\nThis study was conducted at SMA N 1 Surakarta, one \nof the leading public schools in Central Java, representing \nadolescents from diverse socioeconomic and academic \nbackgrounds. Surakarta has also been reported to have \na high prevalence of dysmenorrhoea among female ado -\nlescents, reaching 89.8% among those aged 15–17 years \n[15]. This high prevalence reflects the importance of con-\nducting school-based research in this region to identify \nmodifiable risk factors that could inform early interven -\ntion and menstrual health education programs. Thus, this \nstudy aimed to determine the factors influencing dys -\nmenorrhoea among adolescents in SMA N 1 Surakarta, \nwith the expectation that the findings can be applied in \nschool-based health promotion and early preventive \nefforts for adolescent dysmenorrhea.\nMethods\nStudy design\nThis study employed an analytical observational approach \nwith a cross-sectional design to identify factors associ -\nated with adolescent dysmenorrhea. This research was \nconducted at Sekolah Menengah Atas Negeri (SMA N) 1 \nSurakarta, Central Java, Indonesia. This school, founded \nin 1943, is one of the leading high schools in Surakarta, \nIndonesia.\nPopulation and sample\nThe population in this study consisted of all female stu -\ndents at SMA N 1 Surakarta, Indonesia, with a total of \n222 individuals. This population was chosen because ado-\nlescents in this age group are more likely to experience \nmenstrual problems such as dysmenorrhea, which can \ninterfere with daily activities and school performance.\nAll eligible students were invited to participate in the \nstudy using a total sampling technique. The minimum \nnumber of participants required was determined using \nthe Slovin formula with a 5% margin of error, which \nresulted in a minimum of 141 respondents. This for -\nmula was selected because the total population size was \nknown, while the population variance was unavailable. It \nis commonly used in descriptive cross-sectional research \nto obtain a representative sample when working with a \n\nPage 3 of 8\nBudihastuti et al. Middle East Fertility Society Journal            (2025) 30:65 \nfinite population. To increase accuracy and minimize bias \ndue to possible non-responses, all 222 students who met \nthe inclusion criteria were recruited.\nParticipants included female students aged 10 to 18 \nyears who had experienced menarche and agreed to par -\nticipate voluntarily. Students with chronic or acute medi-\ncal conditions that might affect menstrual patterns, such \nas endocrine disorders, pelvic inflammatory disease, or \nsystemic illness, were not included.\nAll returned questionnaires were checked for com -\npleteness and consistency. Any incomplete or unclear \nresponses were removed during the data cleaning process \nto ensure the accuracy of the final dataset.\nStudy instrument\nPrimary data were obtained through self-administered \nquestionnaires covering demographic information (age, \nBMI, age at menarche, smoking exposure, and family \nhistory) and menstrual characteristics related to dys -\nmenorrhea. The instrument consisted of two main parts. \nThe first part contained 35 items assessing demographic \ndata, menstrual history (regularity, cycle length, duration \nof menstruation), menstrual pain (location, intensity on \na 1–10 scale, duration, and impact on daily activities), \nfamily history of dysmenorrhea, and smoking expo -\nsure. The second part included questions on psychoso -\ncial background, adapted from the International Child \nAbuse Screening Tool for Children (ICAST-C), to iden -\ntify environmental and emotional stress factors poten -\ntially related to menstrual pain. Dysmenorrhea status was \nmeasured using the Verbal Multidimensional Scoring \nSystem (VMSS), which classifies pain as mild, moderate, \nor severe according to its impact on daily activities and \nthe need for medication. Respondents reporting men -\nstrual pain of any intensity were categorized as having \ndysmenorrhea. Content validity of the modified ques -\ntionnaire was reviewed by six obstetrics-gynecology spe -\ncialists and one public-health expert, yielding a Content \nValidity Index (CVI) of 0.91. A pilot test involving twenty \nstudents demonstrated good reliability with a Cronbach’s \nalpha of 0.87.\nStatistical analysis\nThe data were then subjected to univariate, bivariate, \nand multivariate analysis. Bivariate analysis uses the chi-\nsquared statistical test, with a p-value < 0.05 considered \nsignificant. Then, the odds ratio (OR) is calculated, where \nthe OR value and confidence interval (CI) are used to \nassess the significance of the relationship. Variables with \np < 0.25 in the bivariate analysis (Table  2) were included \nin the multivariate logistic regression model to identify \nindependent predictors of dysmenorrhea. Data were ana-\nlyzed using the SPSS 25 edition software (SPSS Inc. Chi -\ncago, IL, USA).\nVariable and measurement\nDependent variable\nDysmenorrhea\nThe dependent variable in this study was dysmenor -\nrhea, defined as menstrual pain experienced during \nmenstruation. Respondents were classified as having \ndysmenorrhea if they reported pain occurring before \nor during menstruation. The variable was categorized \ndichotomously into:\nYes: respondents who experienced menstrual pain,\nNo: respondents who did not experience menstrual \npain.\nThis variable was measured through a structured ques -\ntionnaire using self-reported data from participants.\nIndependent variables\nAge\nAge was recorded as a continuous variable based on the \nrespondent’s age at the time of data collection. Partici -\npants were grouped into categories (15, 16, 17, and 18 \nyears).\nBody Mass Index (BMI)\nBMI is an anthropometric measurement carried out by \ndividing the value of body weight (kg) by the square of \nbody height (m 2). In this study, the numerical scale was \nconverted into ordinal categories. The underweight cat -\negory is if the BMI is < 18.5, while the overweight and \nobese category is if the participant’s BMI is > 24.9. In this \nstudy, the BMI variable was divided into dichotomous \ncategories, namely normal BMI (18.5–24.9) and abnor -\nmal (< 18.5 and > 24.9).\nAge at Menarche\nMenarche was defined as the age when a girl experienced \nher first menstrual period. Early menarche was identified \nwhen menstruation occurred before the age of 12 years \n[16]. The variable was divided into two categories: <12 \nyears and ≥ 12 years.\nMenstrual Regularity\nMenstrual regularity was determined based on partici -\npants’ self-reported menstrual cycle patterns during the \nlast six months.\nRegular: cycles occurring at consistent intervals (21–35 \ndays).\nIrregular: cycles varying by more than seven days from \nmonth to month.\nMenstrual cycle length\nThe menstrual cycle is between the first day of a period \nand the day before the next period begins. The menstrual \n\nPage 4 of 8\nBudihastuti et al. Middle East Fertility Society Journal            (2025) 30:65 \ncycle lasts around 28 days but can vary between 21 and \n35 days. This study divided variables into categorical vari-\nables: menstrual cycles ≤ 27 days and > 27 days.\nDuration of Menstruation\nNormal menstrual duration is approximately 3–7 days. \nThis study divided variables into categorical variables: \nmenstrual duration ≤ 7 days and > 7 days.\nFamily History of Dysmenorrhea\nA family history of dysmenorrhea was defined as the \npresence of similar menstrual pain among first-degree \nfemale relatives, specifically the participant’s mother or \nsister [ 17]. The variable was categorized as no (if there \nwas none) and yes (if there was a family history).\nHistory of Smoking Exposure\nThe low level of active smoking and the increase in pas -\nsive smoking among children make this study take \nvariables regarding cigarette exposure in adolescents \n(second-hand smoke) [ 18]. Exposure to second-hand \nsmoke was evaluated with one question with two answer \noptions: “yes” and “no” .\nEthical consideration\nThis study obtained ethical approval from the Health \nResearch Ethics Committee of Dr. Moewardi Gen -\neral Hospital (Number 994/IV/HREC/2024). Written \ninformed consent was obtained from all participants \nand their parents/guardians. Participants were informed \nabout the study’s objectives, anonymity was ensured, and \nparticipation was voluntary. All collected data were kept \nconfidential and used solely for research purposes.\nResult\nA total of 211 respondents from 222 target populations \nmet the inclusion and exclusion criteria in this study. \nThe prevalence of dysmenorrhoea among female stu -\ndents at SMA N 1 Surakarta was 89.10% (188 out of 211 \nrespondents). Respondents in this study were mostly 16 \nyears old. Half of the research respondents had a nor -\nmal-weight BMI, with 68.20% of respondents experienc -\ning menstruation at the age of more than 12 years. 119 \nrespondents admitted experiencing a menstrual cycle of \n> 27 days, and 59.20% experienced a regular cycle. 63.50% \nof respondents admitted to having a duration of ≤ 7 days. \nMore than half of the respondents (62.10%) had a history \nof close family, such as a mother or sister, experiencing \ndysmenorrhea. The characteristics of the research sub -\njects can be seen in Table 1.\nBased on bivariate analysis in this study, it was found \nthat there was a significant relationship between fam -\nily history and the incidence of dysmenorrhoea. A fam -\nily history of dysmenorrhoea in mothers and sisters has \na 4.09 times higher risk of experiencing dysmenorrhoea \nin adolescents (OR = 4.09; 95% CI = 1.59–10.53; p = 0.002). \nThis study found that factors such as BMI, menarche age, \nmenstrual regularity, menstrual cycle, duration of men -\nstruation, and history of smoking exposure did not have \na significant relationship with the incidence of adolescent \ndysmenorrhea. The results of the bivariate analysis can be \nseen in Table 2.\nThe results of the multivariate analysis (Table  3) \nshowed that adolescents with a positive family history \nof dysmenorrhoea had a significantly higher likelihood \nof experiencing dysmenorrhoea compared with those \nwithout such a history (OR = 5.26; 95% CI: 1.92–14.45; \np = 0.001). Moreover, the menstrual cycle was also sig -\nnificantly associated with dysmenorrhea, where ado -\nlescents with a menstrual cycle length of < 27 days had \na 3.15 times higher risk of experiencing dysmenorrhea \ncompared with those with a normal cycle length ≥ 27 days \n(95% CI = 1.13–8.80; p = 0.029).\nTable 1 Baseline characteristics of participants in SMAN 1 \nSurakarta based on risk factors\nCharacteristics n = 211 (%) Dysmenorrhea\nYes No\nn % n %\nAge (year) 15.67 ± 0.53\n 15 74 (35.10) 60 81.10 14 18.90\n 16 133 (63.00) 125 94.00 8 6.00\n 17 3 (1.40) 3 100.00 0 0.00\n 18 1 (0.50) 1 100.00 0 0.00\nBMI 20.23 ± 3.70\n Abnormal (< 18.5 and > 24.9) 96 (45.50) 84 87.50 12 12.50\n Normoweight (18.5–24.9) 115 (54.50) 105 91.30 10 8.70\nMenarche Age (year)\n < 12 67 (31.80) 61 91.00 6 9.00\n ≥ 12 144 (68.20) 128 88.90 16 11.10\nMenstrual Regularity\n Reguler 125 (59.20) 114 91.20 11 8.80\n Irreguler 86 (40.80) 75 87.20 11 12.80\nMenstrual cycle (day)\n ≤ 27 92 (43.60) 86 93.5 6 6.50\n > 27 119 (56.40) 103 86.6 16 13.40\nDuration of Menstruation (days)\n ≤ 7 134 (63.50) 119 88.8 15 11.20\n > 7 77 (36.50) 70 90.9 7 9.10\nFamily History of Dysmenorrhea\n Yes 131 (62.10) 124 94.70 7 5.30\n No 80 (37.90) 65 81.30 15 18.80\nHistory of Smoking Exposure\n Yes 104 (49.30) 95 91.30 9 8.70\n No 107 (50.70) 94 87.90 13 12.10\nBMI Body mass index\n\nPage 5 of 8\nBudihastuti et al. Middle East Fertility Society Journal            (2025) 30:65 \nDiscussion\nThis study found that the prevalence of dysmenorrhoea \nin teenagers at SMA N 1 Surakarta was relatively high. \nThis is in line with other research conducted in various \ncountries, such as studies in France, where the prevalence \nof dysmenorrhoea in adolescents was 92.9% [ 19], Sweden \n89% [ 20], and Ghana 68.1% [ 19]. A meta-analysis study \nconducted by Wang et al. revealed that the prevalence of \ndysmenorrhoea, especially primary dysmenorrhoea, in \nstudents throughout the world in 2022 was 66.1%, and \nthis prevalence was higher than in previous years [ 14]. \nThis indicates that dysmenorrhoea is a gynecological \nhealth issue that often occurs in women of reproductive \nage, both teenagers and young adults, and needs more \nattention. Other studies involving students, such as those \nin Turkey, were 83.3% [20], Lebanon had a prevalence of \n80.9% [21], Zimbabwe had 75,9% [ 22], Spain 74.8% [ 23], \nEthiopia 51.5% [ 24] and China 41.7% [ 25]. The varia -\ntion in prevalence in several studies in various countries \nis possible due to differences in the demographics of \nresearch respondents, the age criteria of respondents \nused in a study, and socioeconomic factors.\nFamily history of dysmenorrhoea for both mother and \nsister had a significant relationship in this study (OR \n= 5.26; 95% CI: 1.92–14.45; p = 0.001). This aligns with \nprevious research where family history was a risk factor \nfor dysmenorrhoea, with odds ratios varying from 1.68 \nto 3.29 [21, 22, 24, 25]. This is possible due to the role of \ngenetics [ 26], wherein studies of both primary and sec -\nondary dysmenorrhoea populations, chromosome 1p13.2 \nwas identified as being close to the nerve growth factor \nlocus, which is associated with the severity of pain and \ncan increase the body’s sensitivity to pain [ 27]. Apart \nfrom that, the behavior of the family, especially the \nmother, can also influence the perception of pain because \nchildren learn behavior from their mother when suffer -\ning from dysmenorrhea [ 21]. Thus, early education and \ncounseling interventions targeting both adolescents and \nTable 2 Results of bivariate analysis of factors associated with adolescent dysmenorrhoea\nIndependent Variables Dysmenorrhoea OR (CI 95%) p-value\nYes No\nN % n %\nBMI (kg/m2)\n Abnormal (< 18.5 and > 24.9) 84 87.50 12 10.00 1.50\n(0.62–3.64)\n0.368\n Normoweight (18.5–24.9) 105 91.30 10 8.70\nMenarche Age (year)\n < 12 61 91.00 6 9.00 0.79\n(0.29–2.11)\n0.633\n ≥ 12 128 88.90 16 11.10\nMenstrual Regularity\n Reguler 114 91.20 11 8.80 0.66\n(0.27–1.59)\n0.351\n Irreguler 75 87.20 11 12.80\nMenstrual cycle (day)\n ≤ 27 86 93.50 6 6.50 0.45\n(0.17–1.20)\n0.103\n > 27 103 86.60 16 13.40\nDuration of Menstruation (days)\n ≤ 7 119 88.80 15 11.20 1.26\n(0.49–3.24)\n0.630\n > 7 70 90.90 7 9.10\nFamily History of Dysmenorrhea\n Yes 124 94.70 7 5.30 4.09\n(1.59–10.53)\n0.002*\n No 65 81.30 15 18.80\nHistory of Smoking Exposure\n Yes 95 91.30 9 8.70 0.69\n(0.28–1.68)\n0.406\n No 94 87.90 13 12.10\nBased on chi-square test; *, significantly associated at p-value < 0.05, BMI: body mass index\nTable 3 Results of multivariate logistic regression analysis of \npredisposing factors for adolescent dysmenorrhoea\nIndependent Variable OR CI 95% p\nLower \nLimit\nUpper \nLimit\nMenstrual Cycle (< 27 days)a 3.15 1.13 8.80 0.029*\nFamily History of Dysmenorrhea \n(Yes)b\n5.26 1.92 14.45 0.001*\nConstant 13.15 - - 0.000\nn observation = 211\nNagelkerke R2 = 13.7%\n−2 Log likelihood = 126.53\n*Significant at p-value < 0.05\naReference category: menstrual cycle ≥27 days (normal)\nbReference category: no family history of dysmenorrhea\n\nPage 6 of 8\nBudihastuti et al. Middle East Fertility Society Journal            (2025) 30:65 \ntheir mothers are essential to reduce dysmenorrhoea \nseverity and improve pain management strategies.\nOne of the characteristics of menstruation is the men -\nstrual cycle, which appears to have a significant relation -\nship with dysmenorrhoea in adolescents. In this study, a \nmenstrual cycle of >27 days had a 3.15 times higher risk \nof dysmenorrhoea in adolescents. This is in line with pre-\nvious research where menstrual cycles of more than 29 \ndays were more likely to experience dysmenorrhoea than \nthose < 29 days ( p = 0.046) [ 23]. Other literature also \nstates that a menstrual cycle of >35 days is a risk factor \nfor primary dysmenorrhoea in adolescents [28].\nThe American College of Obstetricians and Gynecolo -\ngists (ACOG) and several studies have identified that \nabnormal menstrual cycles are more common in ado -\nlescents. This is caused by the immaturity of the HPO \naxis pathway at puberty, even though adolescents have \nexperienced menarche [ 29]. Puberty begins with the \nfirst release of gonadotropin-releasing hormone (GnRH) \nfrom the hypothalamus, which induces the production of \nfollicle-stimulating hormone (FSH) and luteinizing hor -\nmone (LH) from the anterior pituitary. During puberty, \nthe feedback mechanism and response of the ovarian fol -\nlicles to hormonal stimulation are still not sensitive, caus-\ning the luteal phase of the ovarian cycle to become longer \nand ovulation to fail. The presence of anovulatory cycles \ncauses abnormally long menstrual cycles in adolescents \n[30– 32].\nWomen who experience abnormal menstrual cycle \nlength usually experience anovulation and low progester-\none secretion. Decreased progesterone secretion causes \nexcessive activation of the cyclooxygenase (COX) and \nlipooxygenase (LOX) pathways. This causes excessive \nproduction of prostaglandins, prostacyclins, A2 throm -\nboxane, and leukotrienes, increasing the intensity of dys -\nmenorrhea [33, 34].\nApart from the menstrual cycle, other menstrual \ncharacteristics such as menstrual regularity, menstrual \nduration, and age at menarche were also examined in \nthis study. Different from previous studies, menstrual \nregularity and age at menarche do not have a significant \nrelationship with the incidence of dysmenorrhoea in ado-\nlescents. Several previous studies have shown that men -\nstrual irregularity has a significant relationship with the \noccurrence of dysmenorrhoea [ 19], as well as the age of \nmenarche [20, 22]. A study conducted on 4606 Chinese \nstudents found that age at menarche < 12 years and irreg-\nular menstrual cycles increased the risk of dysmenor -\nrhoea by 1.16 and 1.22 times [ 25]. A possible underlying \nreason is the fact that girls experiencing early menarche \nhave longer exposure to uterine prostaglandins, result -\ning in a higher prevalence of dysmenorrhea [ 35]. One \nof the reasons why the results in this study are different \nfrom other studies may be due to the small number of \nteenagers experiencing menarche who are under 12 years \nold. Our findings are equivalent to the results observed \nby Acheampogn et al., who found no difference in the \nage of menarche between adolescents with dysmenor -\nrhea and non-dysmenorrhea [19]. Further research with a \nlarger and more diverse adolescent population is needed \nto clarify these relationships.\nAnother study also said that irregular menstrual \ncycles increase by up to 2.34 times. This is possible due \nto excessive prostaglandin production in the endome -\ntrium, which causes increased uterine contractions and \narterial vasoconstriction, resulting in ischemic pain [ 24]. \nAlthough the analysis did not find any significance, ado -\nlescents with irregular cycles in this study were 59.2%, \nwhich may indicate that there are still many adolescents \nin this study whose HPO axis is still immature.\nIn this study, we also did not find a significant relation -\nship between menstrual duration and the occurrence of \ndysmenorrhoea in adolescents ( p = 0.630). The relation -\nship between menstrual duration and dysmenorrhoea \nremains contradictory. Several studies say that menstrual \nduration is a risk factor for dysmenorrhea, where men -\nstrual duration ≥ 7 days has a 1.6 times higher chance \nof experiencing dysmenorrhea ( p < 0.05) [ 36]. Another \nstudy in 2015 also found that women who had menstrua -\ntion >5 days had 1.9 times the risk of developing dysmen-\norrhoea [ 35]. However, a recent study in 2019 in Ghana \nconcluded that there was no significant relationship \nbetween menstrual duration and dysmenorrhea ( p >0.01) \n[19]. This study was strengthened by another study in \n2021, which also stated that there was no significant \nrelationship between menstrual duration and dysmenor -\nrhoea (p = 0.56) [21].\nDifferent study results regarding behavioral risk factors \nassociated with dysmenorrhoea were found. Although \nsome studies did not find a relationship between \nunhealthy lifestyle behaviors such as smoking, low BMI \n(< 18.5), and high BMI (>25), some studies reported a \nstrong positive correlation [ 20, 21, 25]. Based on previ -\nous literature, women with a low BMI (thin) or obesity \nhave a high risk of dysmenorrhoea [ 37]. Thin and obese \nadolescents are also known to have a higher degree of \ndysmenorrhea pain compared to groups of normal-\nweight and overweight adolescents [ 38]. However, a sys -\ntematic review and meta-analysis study in 2022 argued \nthat only the underweight group had an increased risk \nof dysmenorrhoea. In contrast, no significant relation -\nship was found for the overweight and obese groups \n[39]. Our study found that there was no significant cor -\nrelation between abnormal BMI and the incidence of dys-\nmenorrhoea, as well as the history of smoking exposure, \nrespectively, p = 0.368 and p = 0.406. Previous evidence \nhas stated that there is a significant relationship between \nwomen who smoke actively and dysmenorrhoea [ 40, \n\nPage 7 of 8\nBudihastuti et al. Middle East Fertility Society Journal            (2025) 30:65 \n41]. However, there is still little literature that discusses \nwomen who are exposed to cigarette smoke/passive \nsmoke. One study found that women who smoke pas -\nsively increased their risk of dysmenorrhoea 1.32 times \n[42].\nThis study has provided a comprehensive overview of \nthe predisposing factors for dysmenorrhea in adoles -\ncents, covering various aspects, starting from menstrual \ncharacteristics to lifestyle. However, researchers are \naware of the limitations of the research. First, the sample \ntaken has the potential not to represent all teenagers in \nthe Surakarta City area because this research was only \nconducted at one center for upper secondary education \n(SMA). Second, the cross-sectional design precludes \ncausal inference and is susceptible to recall bias in self-\nreported menstrual characteristics and lifestyle factors. \nThird, several potentially relevant covariates were not \nmeasured, and the content validity index of the newly \ndeveloped questionnaire was not formally calculated. \nTherefore, long-term, multi-center studies with more \nstandardized risk factor measurements are needed for \nfuture research to estimate the true impact and generate \nrobust evidence.\nConclusion\nThe prevalence of dysmenorrhoea among adolescents at \nSMA N 1 Surakarta was 89.1%. A shorter menstrual cycle \nand a positive family history of dysmenorrhea were sig -\nnificantly associated with dysmenorrhea among adoles -\ncents. These factors should be taken into account when \nassessing adolescents who present with menstrual pain. \nConsidering that dysmenorrhea can interfere with school \nactivities and reduce quality of life, health-care providers \nand school-based health services may consider routine \nassessment of menstrual pain and provision of appropri -\nate management and education on menstrual health.\nAcknowledgements\nThe author would like to thank SMA N 1 Surakarta for permitting research \nand Universitas Sebelas Maret for its financial support through the Penelitian \nHibah Grup Riset (Hgr-UNS) B research scheme.\nAuthors’ contributions\nURB: Conceptualization, Methodology, Supervision, Funding Acquisition, \nWriting – Original Draft, Review & Editing. AL: Data Curation, Formal \nAnalysis, Funding Acquisition, Review & Editing. EM: Investigation, Project \nAdministration, Validation, Funding Acquisition. D: Software, Data Collection, \nFunding Acquisition. AA: Visualization, Literature Review, Funding Acquisition, \nReview & Editing. ASW: Resources, Ethics Approval, Project Administration. \nAAH: Questionnaire Distribution, Statistical Analysis, Writing – Original Draft.\nFunding\nThis research received grant funding from Universitas Sebelas Maret through \nthe Penelitian Hibah Grup Riset (Hgr-UNS) B research scheme with contract \nnumber 194.2/UN27.22/PT.01.03/2024.\nData availability\nThe datasets studied are available from the corresponding author upon \nreasonable request.\nDeclarations\nEthics approval and consent to participate\nThis research has received ethical approval from the ethics committee of Dr. \nMoewardi General Hospital with number 994/IV/HREC/2024. 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