Association between stress and dysmenorrhea among Chinese female adolescent students: a cross-sectional epidemiology study.

A total of 1,449 adolescent females participated in the study. Table  1 outlines the basic characteristics of the participants, among whom 1,038 were reported to have experienced dysmenorrhea, translating to a prevalence rate of 72% (See Table  1 ). The distribution of dysmenorrhea among stratified excluded participants who had abdominal pain even during the non-menstrual period is presented in Supplementary Table 5 . The χ2 test indicated statistically significant differences in age, stress, dietary structure, dairy intake, sleep duration, menstrual cycle, self-reported mental disease, duration of menstruation, and family history of dysmenorrhea within the dysmenorrhea group ( P   0.05) (Supplementary Table 5 ). Table 1 Characteristics of Chinese adolescents surveyed about dysmenorrhea. Variable Overall, N = 1449 Dysmenorrhoea p -value 0 1 N = 411 (28.4) N = 1038 (71.6) Age(years), Mean ± SD 14. 8 ± 1. 5 14. 3 ± 1. 4 14. 9 ± 1. 5 < 0. 001 BMI(kg/m 2 ), Mean ± SD 19. 6 ± 2. 9 19. 6 ± 3. 1 19. 6 ± 2. 9 0.914 Diet structure, n (%) 0. 016  Vegetarian diet 249 (17. 2) 52 (12. 7) 197 (19)  Red diet 700 (48. 3) 210 (51. 1) 490 (47. 2)  White diet 500 (34. 5) 149 (36. 3) 351 (33. 8) Daily milk intake per day, n (%) 0. 002   ≤ 1 682 (47. 1) 167 (40. 6) 515 (49. 6)   > 1 767 (52. 9) 244 (59. 4) 523 (50. 4) Sleep duration, n (%) 0. 017   < 8 1161 (80. 1) 313 (76. 2) 848 (81. 7)   ≥ 8 288 (19. 9) 98 (23. 8) 190 (18. 3) Mental disease self-report, n (%) 0.048  No 1292 (89.2) 377 (91.7) 915 (88.2)  Yes 157 (10.8) 34 (8.3) 123 (11.8) Self-harm, n (%) 0. 194  No 1098 (75. 8) 321 (78. 1) 777 (74. 9)  Yes 351 (24. 2) 90 (21. 9) 261 (25. 1) Stress, n (%) 0.002  No difficulty 174 (12. 0) 63 (15. 3) 111 (10. 7)  Mild difficulty 580 (40. 0) 182 (44. 3) 398 (38. 3)  Moderate difficulty 568 (39. 2) 136 (33. 1) 432 (41. 6)  Severe difficulty 127 ( 8. 8) 30 (7. 3) 97 (9. 3) Age of menarche(years) 0.046   ≤ 11 or > 16 436 (30.1) 108 (26.3) 328 (31.6)  12–16 1013 (69.9) 303 (73.7) 710 (68.4) Menstrual cycle (days) 0. 002    35 93 ( 6.4) 39 (9.5) 54 (5.2) Duration of menstruation(days) 0. 208    8 30 ( 2.1) 9 (2.2) 21 (2) Sanitary napkin usage during menstruation 0. 208    25 127 ( 8.8) 28 (6.8) 99 (9.5) Family history of dysmenorrhea, n (%) < 0. 001  No or don’ t know 808 (55.8) 279 (67.9) 529 (51)  Yes 641 (44.2) 132 (32.1) 509 (49) BMI, body mass index, p values were calculated by comparing characteristics between two groups. Characteristics of Chinese adolescents surveyed about dysmenorrhea. BMI, body mass index, p values were calculated by comparing characteristics between two groups. As shown in Fig.  2 , among the physical symptoms of dysmenorrhea, more than 20% of students reported insomnia, diarrhea, headaches, and nausea symptoms,. and more than 35% reported that they experienced cold hands and feet, abdominal pain, and vertigo, and more than 50% of the students reporting back pain. Fig. 2 Prevalence of physical-behaviour symptoms in dysmenorrhoea adolescent females. Prevalence of physical-behaviour symptoms in dysmenorrhoea adolescent females. The results of the univariate analysis showed that coping with stress with moderate difficulty and severe difficulty, menstrual cycle over 21 days, family history of dysmenorrhea, dietary structure in red meat and vegetables, one serving or less of milk per day, and sleep duration less than 8 h had a higher risk of dysmenorrhea (see Supplementary Table  4 ). A sensitivity analysis, excluding participants with non-menstrual abdominal pain, is presented in Table Supplementary 6 . The results confirm the consistent associations between stress, dietary factors, and dysmenorrhea. The risk of dysmenorrhea after adjusting for covariates is shown in Table  2 . The initial unadjusted analyses indicate a significant association between dysmenorrhea and students who have moderate difficulty (OR 1.8, 95% CI 1.25–2.6) and severe difficulty in stress management (OR 1.84, 95% CI 1.1–3.07), when compared to students who do not have any problem coping with stress. After adjusting for age and BMI, Model 1 showed that the risk increased to 1.86 times for adolescents reporting moderate difficulty (95% CI 1.28–2.7, p  < 0.001), and those with severe stress were 1.97 times more likely to have primary dysmenorrhea (95% CI 1.16–3.32, p  < 0.01). In Model 2, which further adjusted for psycho-behavioral and lifestyle characteristics, the ORs were 1.8 (95% CI 1.23–2.64, p  < 0.001) for moderate difficulty and 1.78 (95% CI 1.02–3.12, p  < 0.04) for severe difficulty. In Model 3, after including menstruation and family history, the OR for experiencing moderate difficulty (compared to no trouble) was 1.66 times (95% CI 1.12–2.47), and severe difficulty was 1.79 times (95% CI 1.01–3.18). Table 2 Association between stress and dysmenorrhoea in the database. Stress n. total n. event % Crude p -value Model 1 p -value Model 2 p -value Model 3 p -value crude.OR 95CI adj. OR 95CI adj. OR 95CI adj. OR 95CI No difficulty 174 111 (63.8) 1(Ref) 1(Ref) 1(Ref) 1(Ref) Mild difficulty 580 398 (68.6) 1.24 (0.87–1.77) 0.234 1.3 (0.9–1.87) 0.159 1.3 (0.9–1.87) 0.165 1.25 (0.86–1.83) 0.247 Moderate difficulty 568 432 (76.1) 1.8 (1.25–2.6) 0.002 1.86 (1.28–2.7) 0.001 1.8 (1.23–2.64) 0.003 1.66 (1.12–2.47) 0.012 Severe difficulty 127 97 (76.4) 1.84 (1.1–3.07) 0.02 1.97 (1.16–3.32) 0.011 1.78 (1.02–3.12) 0.042 1.79 (1.01–3.18) 0.045 P for trend 1449 1038 (71.6)  < 0.001  < 0.001 0.002 0.005 OR, odds ratio; CI, confidence interval; Ref, reference. Model 1 was adjusted for age, and BMI. Model 2 was adjusted for Model1, diet structure, daily milk intake, and sleep time, mental disease, and self-harm. Model 3 was adjusted for Model1, Model2, age of menarche, menstrual cycle, duration of menstruation, sanitary napkin usage during menstruation, and family history. Association between stress and dysmenorrhoea in the database. OR, odds ratio; CI, confidence interval; Ref, reference. Model 1 was adjusted for age, and BMI. Model 2 was adjusted for Model1, diet structure, daily milk intake, and sleep time, mental disease, and self-harm. Model 3 was adjusted for Model1, Model2, age of menarche, menstrual cycle, duration of menstruation, sanitary napkin usage during menstruation, and family history. Subgroup analysis results, depicted in Fig.  3 , show a significant association between moderate difficulty in stress management and dysmenorrhea in participants aged ≥ 15 years (OR 2.42; 95% CI 1.45–4.01), those with BMI ≥ 18.5 (OR 1.87; 95% CI 1.06–3.31), and those without family history of dysmenorrhea (OR 1.71; 95% CI 1.04–2.81). Severe difficulty with stress coping was significantly linked to dysmenorrhea among participants with family history (OR 3.63; 95% CI 1.2–11.0). No significant association was observed in participants aged < 15 years or in those with BMI < 18.5. Fig. 3 Association between stress and dysmenorrhea. Each stratification was adjusted for age, BMI, diet structure, daily milk intake, and sleep time, mental disease, and self-harm, age of menarche, menstrual cycle, duration of menstruation, sanitary napkin usage during menstruation, and family history except the stratification factor itself. Squares indicate odds ratios(ORs). with horizontal lines indicating 95% Cls. Diamonds indicate overall ORs, with outer points of the diamonds indicating 95% Cls. Association between stress and dysmenorrhea. Each stratification was adjusted for age, BMI, diet structure, daily milk intake, and sleep time, mental disease, and self-harm, age of menarche, menstrual cycle, duration of menstruation, sanitary napkin usage during menstruation, and family history except the stratification factor itself. Squares indicate odds ratios(ORs). with horizontal lines indicating 95% Cls. Diamonds indicate overall ORs, with outer points of the diamonds indicating 95% Cls. Table S7 and Fig. S1 summarize the results of the sensitivity analyses. Multifactorial analyses show a consistent link between moderate difficulties in stress management and dysmenorrhea, proving that these results are true across a number of different models. Subgroup analyses further validate the stability of these associations across age, BMI, and family history, underscoring the reliability of our results.

A cross-sectional study was conducted in Shenzhen, Guangdong Province, China, from April to December 2023. A two-step random, stratified, cluster-based sampling method was applied to investigate the health status of adolescent female students. First, schools were stratified by their geographic location into central and non-central areas, and by educational level into junior middle schools, senior high schools, and vocational high schools. This stratification was designed to ensure a representative cross-section of the student population, considering the diverse socio-economic backgrounds present across the urban landscape of Shenzhen. Second, within the stratified schools, specific grades were targeted for cluster sampling: Grade 8 in middle schools and Grades 10 and 11 in high schools. This selection aimed to address and reduce potential biases associated with the onset of puberty and academic pressures, particularly those relevant to these age groups. The inclusion criterion for this study was middle and high school girls, and the exclusion criterion was students who had not yet reached menarche. The Medical Ethics Committee of Shenzhen Futian District Maternal and Child Health Care Hospital approved this study. The study adhered to the principles of the Declaration of Helsinki. Before the survey began, we obtained informed consent from all participants and their parents for respondents under the age of 18 to ensure that participants volunteered to participate and fully understood the study content. And their anonymity was assured by assessing each of them using a code number useful in the analysis process. Our survey team worked and communicated well with the schools in the early stages and was supported by professionally trained staff on-site. The questionnaires were self-administered by the participants, with trained personnel available on-site to assist with any questions. This approach ensured the collection of high-quality data and a high response rate. The formula is calculated according to the sample size: \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$n = \left( {\frac{{Z_{\alpha /2} }}{\delta }} \right)^{2} p(1 - p)$$\end{document} . α is a type I error. p is the prevalence of dysmenorrhea. δ is the allowable error. The confidence level is 1 − α = 0.95, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$Z_{\alpha /2}$$\end{document}  = 1.96. Approximately 60–90% of adolescents suffer from dysmenorrhea, according to the literature 18 , 19 . A two-sided test was conducted with a significance level of 0.05 and a tolerance level of 3%, and a sample size of N = 1056 was calculated. According to the actual situation, the lost visit rate can be adjusted within the range of 20% Murray, a minimum of 1320 adolescent female students would need to be surveyed. Initially, 1687 individuals were recruited for our study. A total of 1530 valid responses were received, resulting in a 90.69% effective response rate. According to the WHO's definition of adolescents, 10 to 19 years old are included in our analysis 20 . The inclusion and exclusion criteria are as follows: Inclusion criteria: Girls aged 10–19 who are enrolled in middle and high schools in Shenzhen and have already experienced menarche. Exclusion criteria: Those who have not yet experienced menarche; those with a confirmed diagnosis of uterine fibroids, adenomyosis, endometriosis, infertility, or other diseases potentially related to the study; those with language or cognitive impairments affecting communication; those who refuse to participate in the study; and respondents with missing key variables. Based on the exclusion of secondary dysmenorrhea and respondents with missing key variables, a total of 1449 samples were ultimately included (See Fig.  1 ). Fig. 1 Sample inclusion and exclusion flowchart. Sample inclusion and exclusion flowchart. The survey used in this study was specifically designed for this research. The development process included a literature review, expert discussions, and pilot testing to ensure the content validity and reliability of the survey. The questionnaire comprises 26 questions divided into three sections(see Supplementary file 1 ): Menstruation information questionnaire: this questionnaire consisted of items related to demographic information (age, height, and weight), as well as menstruation characteristics 21 . The menstruation characteristics section included one item on age at menarche, one item on menstrual cycle, one item on duration of menstruation, and one item on sanitary napkin usage during menstruation. The dysmenorrhea pattern consisted of one item assessing the frequency of dysmenorrhea, one item evaluating the family history of dysmenorrhea, and items examining the physical-behavioral and psychological symptoms associated with dysmenorrhea. Additionally, there was one item addressing unexplained abdominal pain during non-menstrual time. Eating and sleeping: potential confounding variables were the quantity of dairy consumed per day, the number of hours of sleep per day, and the dietary structure. Sleep duration was primarily self-reported as the continuous nighttime sleep period. Dietary structure was assessed by evaluating differences in meat consumption among adolescents, specifically by inquiring about the intake of red and white meats. Red meat typically refers to meat that is rich in myoglobin and darker in color, such as pork, beef, and lamb, while white meat refers to meat that is lighter in color and contains less myoglobin, such as fish, chicken, and other poultry. Psychological and behavioral factors: the survey included one question about self-reporting of mental illness and one question about self-harm, referring to the content of the questionnaire designed by the National Center for Women and Children’s Health, Chinese Center for Disease Control and Prevention 22 . In this study, mental disease were assessed based on whether respondents reported ever having been diagnosed with a psychological disorder. Five options were provided: (1) Depression, (2) Anxiety, (3) Bipolar disorder, (4) Other (where respondents self-reported any other type of psychological disorder), and (5) No diagnosis of a psychological disorder. Stress: the Perceived Stress Scale-4 (PSS-4) is a simplified version of the PSS and consists of four questions from the original questionnaire. This study used the short version and assessed whether individuals felt they were unable to cope with things in their lives, implying confidence in one's ability to deal with problems or whether difficulties are insurmountable. The time period for this questionnaire has been changed from the past month to the last year. In our study, we conducted a small-scale survey involving 36 participants to examine the relationship between responses on the full PSS-4 and a single-item question focused on stress(See Supplementary Tables  1 – 3 ). It indicated good consistency and supported the potential use of the single-item approach in settings where a quick and extensive assessment is preferable or necessary. The item posed the question: In the past year, when you experienced stress, how did you cope? Please rate the difficulty of managing your stress: (1) No difficulty, (2) Mild difficulty, (3) Moderate difficulty, and (4) Severe difficulty. Menstruation information questionnaire: this questionnaire consisted of items related to demographic information (age, height, and weight), as well as menstruation characteristics 21 . The menstruation characteristics section included one item on age at menarche, one item on menstrual cycle, one item on duration of menstruation, and one item on sanitary napkin usage during menstruation. The dysmenorrhea pattern consisted of one item assessing the frequency of dysmenorrhea, one item evaluating the family history of dysmenorrhea, and items examining the physical-behavioral and psychological symptoms associated with dysmenorrhea. Additionally, there was one item addressing unexplained abdominal pain during non-menstrual time. Eating and sleeping: potential confounding variables were the quantity of dairy consumed per day, the number of hours of sleep per day, and the dietary structure. Sleep duration was primarily self-reported as the continuous nighttime sleep period. Dietary structure was assessed by evaluating differences in meat consumption among adolescents, specifically by inquiring about the intake of red and white meats. Red meat typically refers to meat that is rich in myoglobin and darker in color, such as pork, beef, and lamb, while white meat refers to meat that is lighter in color and contains less myoglobin, such as fish, chicken, and other poultry. Psychological and behavioral factors: the survey included one question about self-reporting of mental illness and one question about self-harm, referring to the content of the questionnaire designed by the National Center for Women and Children’s Health, Chinese Center for Disease Control and Prevention 22 . In this study, mental disease were assessed based on whether respondents reported ever having been diagnosed with a psychological disorder. Five options were provided: (1) Depression, (2) Anxiety, (3) Bipolar disorder, (4) Other (where respondents self-reported any other type of psychological disorder), and (5) No diagnosis of a psychological disorder. Stress: the Perceived Stress Scale-4 (PSS-4) is a simplified version of the PSS and consists of four questions from the original questionnaire. This study used the short version and assessed whether individuals felt they were unable to cope with things in their lives, implying confidence in one's ability to deal with problems or whether difficulties are insurmountable. The time period for this questionnaire has been changed from the past month to the last year. In our study, we conducted a small-scale survey involving 36 participants to examine the relationship between responses on the full PSS-4 and a single-item question focused on stress(See Supplementary Tables  1 – 3 ). It indicated good consistency and supported the potential use of the single-item approach in settings where a quick and extensive assessment is preferable or necessary. The item posed the question: In the past year, when you experienced stress, how did you cope? Please rate the difficulty of managing your stress: (1) No difficulty, (2) Mild difficulty, (3) Moderate difficulty, and (4) Severe difficulty. All normally distributed continuous variables were stated as mean ± SD. Categorical variables were reported as frequencies (%). T-test was performed to assess differences between groups for continuous variables with normal distribution and Wilcoxon rank sum test for continuous variables without normal distribution. The chi-square test and Cochran-Armitage trend test were for the categorical variables. Univariate and multivariable logistic regression models were employed to determine the connection between stress and dysmenorrhea. Four separate models were created to study the association between stress and dysmenorrhea. Model 1 was adjusted for age and body mass index (BMI). Model 2 improved upon this by introducing changes for meal structure, daily milk intake, sleep time, mental disorders, and self-harm. Model 3 additionally contained changes for age of menarche, menstrual cycle, duration of menstruation, sanitary napkin usage during menstruation, and family history. In addition, interaction and subgroup analyses were done according to age, BMI, and family history using logistic regression models. Interaction among subgroups was assessed using the likelihood ratio test (P for interaction 1). To confirm the robustness of our findings, we ran focused sensitivity analyses. Specifically, to reduce the potential influence of non-primary dysmenorrhea, we removed 66 subjects who reported abdominal pain outside their menstrual periods. We then re-analyzed the remaining dataset with univariate and multivariate analyses, as well as subgroup analyses, presenting the results in forest plots. All statistical analyses were generated with the R software ( http://www.R-project.org ; Version 4.2.1) and Free Statistics software Version 1.9 ( www.freestatistics.tk ). The criteria for statistical significance were p  < 0.05 or adjusted p  < 0.05.

This study described the prevalence and symptoms of dysmenorrhea and explored the relationship between stress management and dysmenorrhea among Chinese adolescent females in Shenzhen City. More than 70% of the participants reported experiencing dysmenorrhea, and around 40% of people feel moderate to severe difficulty when dealing with stress. Concerning dysmenorrhea symptoms in Chinese adolescent females, over half of participants reported low back and leg pain, and more than 35% reported vertigo, cold hands and feet, and stomach pain. Notably, a positive correlation was identified between the capability of stress and dysmenorrhea. Participants who reported moderate difficulty in stress were 1.66 more likely to suffer dysmenorrhea, which was also the case of participants who reported severe difficulty, for whom the likelihood was 1.79, even controlling confounding variables. In our study, the prevalence of dysmenorrhea among adolescent females (72%) corresponded with the results of the worldwide prevalence of dysmenorrhoea, which ranges from 20 to 90% 23 . The prevalence of dysmenorrhea in our study population, which is situated between the rates reported in other developing countries, is higher than that reported among adolescent female students in Ethiopia at 64.7% 24 , yet lower than the 82% observed in Nigeria 25 . Different operational definitions of dysmenorrhoea may account for the differences in reported prevalence. In univariate regression analysis, sleep duration, self-reported psychological disorder, diet structure, and daily milk intake were found to be significantly associated with an increased incidence of dysmenorrhoea. But BMI was not significantly associated with an increased occurrence of dysmenorrhoea. In this study, sleeping more than 8 h was associated with a lower occurrence of dysmenorrhea, which consisted of two systematic reviews that found that longer sleep duration was protective against dysmenorrhea 26 . In addition, psychological disorders such as depression and anxiety are reported as important factors associated with dysmenorrhea. Duman et al. found that adolescents with higher depressive symptoms are at greater risk of experiencing menstrual symptoms or more severe symptoms across adolescence 27 . We also found a significant association between self-reported psychological disorder and higher odd rates of dysmenorrhea. Outstandingly, this study found a positive correlation was identified between the capability to manage stress and dysmenorrhea. Those with severe difficulty in capability of stress manage had a 1.79 times higher rate of dysmenorrhea than those with no difficulty in stress management. This might have a connection with the fact that those female adolescents who are more able to cope with stress would have more appropriate corresponding treatments and, thus, a greater ability to alleviate dysmenorrheal symptoms 28 . In some studies, psychological stress might have a bidirectional association with dysmenorrhea 29 . In other words, experiencing monthly repeated menstrual pain might increase the risk of experiencing stress, and vice versa. The possible mechanism of the relationship between stress and dysmenorrhea may be that stress reflects individual psychological tolerance and pain perception 30 . In some cases, this psychological stress exacerbates the severity of menstrual pain 31 . In a critical review in 2015, Iacovides et al. proposed that patients with severe dysmenorrhea have increased pain sensitivity, which cannot be explained by increased prostaglandin production alone 32 . The probable alternative explanation is central sensitivity to stress, which is an abnormal stress mechanism with an intensified peripheral response to stress 33 . The cyclic nature of menstruation raised the hypothesis that dysmenorrhea might be due to increased sensitivity to stress 34 . Therefore, experiencing dysmenorrhea not only has a physical aspect but can also have a psychological aspect, which influences the development of psychological stress but can also be influenced by these conditions. The current study has several strengths, including its representative prospective design, high participation rate, and potential to expand our understanding of the relationship between stress coping and primary dysmenorrhea. However, because this study is cross-sectional, it can only reveal associations rather than causal relationships. Secondly, the study did not use validated questionnaires to assess stress coping, diet, and physical activity; future research could employ more effective scales to further evaluate the relationship between stress and dysmenorrhea. Thirdly, although this study explored the stress coping mechanisms and primary dysmenorrhea issues among adolescent females in Shenzhen, these findings were based on self-reported data, and their generalizability to a broader Chinese context still requires further investigation.

This study revealed a significant correlation between higher levels of stress and the prevalence of dysmenorrhea among adolescents, underscoring the critical role of stress management in public health strategies aimed at mitigating menstrual discomfort. Given the methodological constraints, these results warrant cautious interpretation and highlight the imperative for further population-based research to validate these initial insights. This investigation paves the way for future public health studies to explore effective interventions for dysmenorrhea, emphasizing the necessity of holistic approaches that address both physiological and psychological aspects of menstrual health.

Dysmenorrhea, the most prevalent complaint among adolescent girls and women of reproductive age, represents a major women’s health burden and constitutes a significant public health issue globally 1 . Also known as painful menstruation, it is characterized by uterine cramps occurring before or during menstruation 2 . Dysmenorrhea has been recognized as a predominant contributor to pelvic pain and various menstrual irregularities, including irregular menstrual cycles, abnormal flow volume, and pain-associated alterations in bleeding patterns among women of reproductive age 3 . Menstrual cramps occurring in the absence of any pelvic pathology are classified as primary dysmenorrhea, predominantly affecting women younger than 20 years old 4 . In adolescents, dysmenorrhea, particularly primary dysmenorrhea, poses a significant public health challenge, with prevalence ranging from 19.4 to 79.9% in China 1 . Numerous studies indicate that severe menstrual pain contributes to school absenteeism and imposes restrictions on other daily activities 7 . Dysmenorrhea has long been associated with socioeconomic implications due to the increased demand for medical care and its associated costs, as well as the diminished capacity of adolescents to perform routine tasks 8 . Stress, defined as the perception of an inability to manage life's demands, holds significant importance in neuroscience research because of its profound and intricate effects on physiological processes 9 . According to the allostatic load model, although stress responses are vital for survival, they may contribute to the development of illness over time 10 . During adolescence—a critical phase for endocrine development—the potential underlying mechanism may involve the hypothalamic–pituitary–adrenal (HPA) axis 11 . While the HPA axis primarily serves as a general stress response system, cortisol can exert substantial effects on other bodily systems, including reproductive health 12 . Stress can be quantitatively assessed through physiological markers such as cortisol levels, heart rate variability, and blood pressure, which serve as reflections of the body's physiological response to stress. Additionally, psychological assessments, including the Perceived Stress Scale (PSS) and the Stress Response Inventory (SRI) are utilized to evaluate individual psychological stress states 13 , 14 . A variety of physical and environmental risk factors for dysmenorrhea have been documented, including an earlier age at menarche, a family history of dysmenorrhea, elevated body mass index (BMI), and other social determinants 1 , 15 . Recent studies have indicated a positive correlation between psychological factors, particularly work-related or life-related stress, and the incidence of dysmenorrhea 16 , 17 . Nevertheless, despite the acknowledged significance of stress as a contributing factor, there is a paucity of research specifically addressing adolescent stress. Furthermore, while some studies have examined this issue within Chinese population, investigations into the relationship between the capability of stress management and dysmenorrhea among Chinese female adolescents remain exceedingly limited. Conducted in the diverse social context of Shenzhen, this study employed a stratified cluster sampling approach in conjunction with the short version of the Perceived Stress Scale (PSS-4) and a custom-designed questionnaire to systematically explore the association between stress and dysmenorrhea among adolescent females, thereby filling a research gap in this specific population and regional context. This study proposes a retrospective cross-sectional analysis to examine the association between stress and the prevalence of dysmenorrhea among Chinese adolescent females. By concentrating on this comprehensive, culturally, and demographically specific research, the study aims to illuminate culturally specific stress factors and their management, thereby enhancing understanding of these aspects, focusing on stress mechanisms and their relationship with dysmenorrhea, and contributing valuable insights into its management and potential intervention strategies.

Supplementary Information. Supplementary Information.