Association Between Exercise Habits,Including an Exercise Partner,and Menstrual Status in a Japanese Population

Abstract

Introduction:

Primary dysmenorrhea is a common condition in young women and substantially impairs quality of life. While exercise has preventive effects on many diseases, its association with dysmenorrhea in Asian populations remains inconsistent. We therefore investigated the relationship between exercise habits, including the presence of an exercise partner, and menstrual status, such as pain, medication use, and cycle regularity, in a young Japanese population.

Methods:

A total of 4892 female university students were included in this analysis. Information regarding menstrual status (regularity, pain severity, and use of medication) and exercise habits (exercise frequency, exercise intensity, and exercise partners) was obtained using a self-administered questionnaire. In the analysis, students who reported no regular exercise were used as the reference group.

Results:

Low (1–2 times/month) and moderate exercise frequency (1–3 times/week), light, moderate, intense exercise, and exercising with groups or friends was independently and inversely associated with menstrual pain (adjusted odds ratio [OR]: low exercise: 0.86 [95% confidence interval (CI): 0.75–0.99], moderate exercise: 0.73 [95% CI: 0.62–0.85], light: 0.82 [95% CI: 0.71–0.96], moderate: 0.85 [95% CI: 0.73–0.98], intense: 0.81 [95% CI: 0.68–0.97], groups: 0.81 [95% CI: 0.68–0.97], and friends: OR: 0.68 [95% CI: 0.56–0.82]). Similarly, exercising with friends was independently and inversely associated with the use of medication for pain (adjusted OR: 0.79 [95% CI: 0.66–0.96]). Exercise habits including exercise partner was not associated with menstrual cycle.

Conclusions:

Among young Japanese women, exercise habits exercising with partners were independently and inversely associated with menstrual pain.

Keywords

exercise dysmenorrhea young Japanese population menstrual pain

Introduction

Primary dysmenorrhea, defined as painful uterine cramps without pelvic pathology occurring just before or during menstruation, is the most common gynecological disorder in women and is associated with impaired quality of life, mood, and sleep, highlighting the medical importance of adequate pain control, often with nonsteroidal anti-inflammatory drugs.^1,2 Exercise offers numerous health benefits and has been recommended as a treatment for primary dysmenorrhea; however, the evidence supporting its effectiveness in alleviating primary dysmenorrhea remains inconclusive. Several systematic reviews and meta-analyses have demonstrated that physical activity (PA) has a protective effect on menstrual pain.^3–6 However, the association between exercise and dysmenorrhea remains inconsistent in Asian populations. Studies from Korea, Indonesia, India, Thailand, and Japan have shown an inverse association between exercise and dysmenorrhea.^7–11 Conversely, no such association was found in studies from India, Saudi Arabia, and China.^12–14 Evidence on the relationship between exercise habits and dysmenorrhea in the Japanese population remains limited.

Exercising with others may have a stronger beneficial effect on health.^15–20 After adjustment for PA, exercise partner is independently associated with health status.¹⁷ Additionally, exercise with partner was significantly associated with functional dyspepsia,¹⁸ irritable bowel syndrome,¹⁹ and constipation.²⁰ Association between functional gastrointestinal disorders and menstrual pain was reported.^21,22 Thus, we hypothesized that exercising with others may also alleviate menstrual pain through similar mechanisms. However, no studies have investigated the association between having an exercise partner and dysmenorrhea. To contribute to the growing body of evidence, we aimed to evaluate the association between self-reported exercise habits, including exercise partners, and menstrual status, including menstrual pain, medication use and menstrual cycle regularity in a young Japanese population.

Materials and Methods

Study population

This study enrolled 4951 students who underwent a health examination at Ehime University (Ehime, Japan) between April 2015 and April 2017. A specific questionnaire pertaining to dysmenorrhea was distributed to all subjects at the time of their health checkup. After excluding one subject due to incomplete data and 58 subjects with amenorrhea for 3 months or more, the final analysis included 4892 participants, all of whom were assessed for exercise habits, menstrual pain, menstrual cycle status, and use of medication for pain (Fig. 1).

FIG. 1.

The study population.

Ethics approval and consent to participate

All subjects were provided with the opportunity to opt out, and the study protocol was developed in accordance with the ethical guidelines of the Declaration of Helsinki. This study was approved by the ethics committee of Ehime University Graduate School of Medicine (approval no. 1610012).

Questionnaire measurements

Information on age, body mass index (BMI), drinking, and smoking was collected using a self-administered questionnaire. Weight was measured with participants wearing light clothing, and BMI was calculated as weight in kilograms divided by height in meters squared. Current smoking was defined as positive if a participant reported smoking at least one cigarette per day. Current drinking was defined as positive if a participant reported a habit of consuming alcoholic beverages.

Assessment of menstrual irregularity, menstrual pain, and medication use

A self-administered questionnaire was used to assess menstrual cycle and dysmenorrhea using the following questions: (1) menstrual cycle: “How is your menstrual cycle?” (none for 3 months or more, irregular, mainly regular), (2) menstrual pain: “How strong is your menstrual pain?” (none, mild, sometimes severe, severe), (3) medication for menstrual pain: “How often do you use medication for menstrual pain?” (never, sometimes, often).

Assessment of exercise habits, including presence/absence of exercise partners

A self-administered questionnaire was used to assess exercise habit including frequency of exercise, main exercise intensity and exercise partner, described in detail in the preceding article^18–20 and supplementary file 1: (1) frequency of exercise: none, 1–2 times a month, 1–3 times a week, 4 or more times a week; (2) intensity of main exercise: no exercise, light exercise, moderate exercise, intense exercise; (3) exercise partners: no exercise, group, friends, alone.

Statistical analysis

Participants’ exercise habits were categorized across three dimensions. Exercise frequency was grouped into four levels: no exercise (reference group), infrequent (1–2 times per month), moderate (1–3 times per week), and frequent (4 or more times per week). Exercise intensity was similarly divided into four categories: no exercise (reference), light, moderate, and vigorous. The context of exercise participation was also classified into four groups: exercising alone, with friends, with a group, or not exercising (reference). To assess associations between exercise behaviors and menstrual health outcomes—including menstrual cycle regularity, menstrual pain, and use of analgesic medication for menstrual discomfort—logistic regression models were applied. Crude odds ratios (ORs) and corresponding 95% confidence intervals (CIs) were calculated. Multivariable logistic regression analyses were also conducted to adjust for potential confounders identified a priori: age, BMI, alcohol consumption, and smoking status.^23–26 The trend of the association was assessed using a logistic regression model, in which consecutive integers were assigned to the categories of exercise habit variables (frequency and intensity). All statistical analyses were performed using SAS software version 9.4 (SAS Institute Inc., Cary, NC, USA). Statistical significance was determined using two-sided tests, with p-values less than 0.05 considered statistically significant.

Results

Subject characteristics

Table 1 shows the characteristics of participants. The mean age and BMI were 19.9 ± 3.0 years and 20.88 ± 2.75 kg/m², respectively. The prevalence of menstrual pain (classified as “sometimes severe” or “severe”), use of medication for pain (sometimes of often) and menstrual cycle (irregular) was 54.8%, 48.5%, and 14.0%, respectively.

Table 1.

Clinical Characteristics of 4892 Study Participants

	Total (N = 4892)
Age, years, mean ± SD	19.9 ± 3.0
BMI, kg/m², mean ± SD	20.88 ± 2.75
Smoking (%)	52 (1.1)
Drinking (%)	308 (6.3)
Exercise habit
Frequency of exercise habit
None, %	2075 (42.4)
1–2 times/month, %	1289 (26.4)
1–3 times/week, %	934 (19.1)
4 or more times/week, %	594 (12.1)
Intensity of exercise
None, %	2075 (42.4)
Light exercise, %	1015 (20.8)
Moderate exercise, %	1182 (24.2)
Intense exercise, %	620 (12.7)
Exercise with
None, %	2075 (42.4)
Group, %	596 (12.2)
Friends, %	555 (11.4)
Alone, %	1666 (34.1)
Menstruation
Menstrual pain
No, n, %	781 (15.9)
Mild, n, %	1433 (29.3)
Sometimes severe or severe, n, %	2679 (54.8)
Medication for pain
Never, n, %	2,519 (51.5)
Sometimes or often, n, %	2373 (48.5)
Menstrual cycle
Mainly regular, n, %	4205 (86.0)
Irregular, n, %	687 (14.0)

BMI, body mass index.

Association between exercise habits and menstrual pain

Table 2 presents the crude and adjusted ORs and 95% CIs for menstrual pain (sometimes severe or severe pain) in relation to exercise habits. After adjusting for age, BMI, drinking, and smoking, low (1–2 times per month) and moderate (1–3 times per week) frequency of exercise was independently and inversely associated with menstrual pain (adjusted OR; low: 0.86 [95% CI: 0.75–0.99] and, moderate: 0.73 [95% CI: 0.62–0.85], p for trend; p = 0.014). Light, moderate, and high intensity exercise was independently and inversely associated with menstrual pain after adjustment for confounding factors (adjusted ORs: light: 0.82 [95% CI: 0.73–0.98], moderate: 0.85 [95% CI: 0.73–0.98], and high: OR: 0.81 [95% CI: 0.68–0.97], p for trend = 0.006). Exercising with groups or friends was independently and inversely associated with menstrual pain (adjusted OR: with groups: 0.81 [95% CI: 0.68–0.97]; with friends: OR: 0.68 [95% CI: 0.56–0.82]). Exercising in solitude was not associated with menstrual pain.

Table 2.

Association Between Exercise Habits and Menstrual Pain (Sometimes Severe or Severe)

Variable	Prevalence (%)	Crude OR (95% CI)	Adjusted OR (95% CI)
Menstrual pain (Sometimes severe or severe)
Frequency of exercise habit
None, %	1193/2075 (57.5)	1.00	1.00
1–2 times/month, %	694/1289 (53.8)	0.86 (0.75–0.99)	0.86 (0.75–0.99)
1–3 times/week, %	461/934 (49.4)	0.72 (0.62–0.84)	0.73 (0.62–0.85)
4 or more times/week, %	331/594 (55.7)	0.93 (0.77–1.12)	0.94 (0.78–1.13)
p for trend			0.014
Intensity of exercise
None, %	1193/2075 (57.5)	1.00	1.00
Light exercise, %	530/1015 (52.2)	0.81 (0.70–0.94)	0.82 (0.71–0.96)
Moderate exercise, %	631/1182 (53.4)	0.85 (0.73–0.98)	0.85 (0.73–0.98)
Intense exercise, %	325/620 (52.4)	0.81 (0.68–0.98)	0.81 (0.68–0.97)
p for trend			0.006
Exercise with
None, %	1193/2075 (57.5)	1.00	1.00
Group, %	311/596 (52.2)	0.81 (0.67–0.97)	0.81 (0.68–0.97)
Friends, %	265/555 (47.8)	0.68 (0.56–0.82)	0.68 (0.56–0.82)
Alone, %	910/1666 (54.6)	0.89 (0.78–1.01)	0.90 (0.79–1.02)

Adjusted for age, BMI, drinking, and smoking.

CI, confidence interval; OR, odds ratio.

Association between exercise habits and medication for pain

Table 3 presents the crude and adjusted ORs and 95% CIs for use of medication for pain in relation to exercise habits. The association between frequency of exercise and use of medication for menstrual pain was not significant. After adjusting for age, BMI, drinking, and smoking, high intensity exercise was independently and inversely associated with the use of medication for pain (adjusted OR: high intensity exercise: 0.82 [95% CI: 0.69–0.99], p for trend = 0.020). Exercising with friends was independently and inversely associated with the use of medication for pain (adjusted OR: with friends: OR 0.87 [95% CI: 0.66–0.96]).

Table 3.

Association Between Exercise Habits and Medication for Pain

Variable	Prevalence (%)	Crude OR (95% CI)	Adjusted OR (95% CI)
Use of medication for pain
Frequency of exercise habit
None, %	1049/2075 (50.6)	1.00	1.00
1–2 times/month, %	609/1289 (47.3)	0.88 (0.76–1.01)	0.88 (0.76–1.01)
1–3 times/week, %	441/934 (47.2)	0.88 (0.75–1.02)	0.89 (0.76–1.04)
4 or more times/week, %	276/594 (46.1)	0.84 (0.70–1.005)	0.85 (0.71–1.03)
p for trend			0.044
Intensity of exercise
None, %	1049/2075 (50.6)	1.00	1.00
Light exercise, %	480/1015 (47.3)	0.88 (0.76–1.02)	0.89 (0.77–1.04)
Moderate exercise, %	561/1185 (47.5)	0.88 (0.77–1.02)	0.88 (0.77–1.03)
Intense exercise, %	283/620 (45.7)	0.82 (0.69–0.98)	0.82 (0.69–0.99)
p for trend			0.020
Exercise with
None, %	1049/2075 (50.6))	1.00	1.00
Group, %	279/596 (46.8)	0.86 (0.72–1.03)	0.87 (0.72–1.04)
Friends, %	250/555 (45.1)	0.80 (0.66–0.97)	0.79 (0.66–0.96)
Alone, %	795/1666 (47.7)	0.89 (0.79–1.02)	0.91 (0.80–1.03)

Adjusted for age, BMI, drinking and smoking.

Association between exercise habits and menstrual cycle

Table 4 presents the crude and adjusted ORs and 95% CIs for menstrual cycles in relation to exercise habits. No significant associations between exercise frequency, intensity, or exercise partner and irregular menstrual cycle were found.

Table 4.

Association between Exercise Habits and Menstrual Cycle

Variable	Prevalence (%)	Crude OR (95% CI)	Adjusted OR (95% CI)
Menstrual cycle (regular cycle)
Frequency of exercise habit
None, %	306/2075 (14.8)	1.00	1.00
1–2 times/month, %	161/1289 (12.5)	0.83 (0.67–1.011)	0.83 (0.68–1.02)
1–3 times/week, %	141/934 (15.1)	1.03 (0.83–1.27)	1.04 (0.83–1.28)
4 or more times/week, %	79/594 (13.3)	0.89 (0.68–1.15)	0.90 (0.69–1.17)
p for trend			0.67
Intensity of exercise
None, %	306/2075 (14.8)	1.00	1.00
Light exercise, %	125/1015 (12.3)	0.81 (0.65–1.01)	0.82 (0.66–1.03)
Moderate exercise, %	165/1182 (14.0)	0.94 (0.76–1.15)	0.94 (0.77–1.15)
Intense exercise, %	91/620 (14.7)	0.99 (0.77–1.28)	1.01 (0.78–1.29)
p for trend			0.83
Exercise with
None, %	306/2075 (14.8)	1.00	1.00
Group, %	79/596 (13.3)	0.88 (0.67–1.15)	0.89 (0.68–1.16)
Friends, %	77/555 (13.9)	0.93 (0.71–1.21)	0.94 (0.71–1.22)
Alone, %	225/1666 (13.5)	0.90 (0.75–1.09)	0.91 (0.76–1.10)

Adjusted for age, BMI, drinking and smoking.

Discussion

In the present study, exercise frequency and intensity, and having an exercise partner, were independently and inversely associated with menstrual pain. To the best of our knowledge, this is the first study to demonstrate an inverse association between exercising with a partner and menstrual pain in a young Japanese population.

Several studies have reported the association between exercise and dysmenorrhea in Asian populations; however, findings remain inconsistent. Interventional studies showed that exercise alleviated primary dysmenorrhea. Structured exercise,⁹ yoga,¹⁰ regular exercise,¹¹ and Zumba exercise¹² was effective for menstrual pain reduction. Observational findings, however, are heterogeneous. An Indonesian study found that PA was significantly inversely associated with primary dysmenorrhea based on The Menstrual Distress Questionnaire.⁸ No association between exercise and dysmenorrhea was found in an Indian study of 621 participants,¹² a Saudi Arabian study of 376 female medical students,¹³ and a Chinese study of 4616 participants.¹⁴ Caffeine intake¹³ and low BMI, early menarche, maternal history, irregular cycles, and breakfast skipping¹⁴ were associated with dysmenorrhea. These discrepancies may be explained, at least in part, due to differences in the definition of dysmenorrhea (visual analogue scale or questionnaire), study design (observational or interventional), race, sample size, methods of assessing exercise habits (frequency or metabolic equivalent of task), and the potential confounding factors.

The underlying mechanism linking PA and menstrual pain remains unclear. Menstrual pain is thought to result from uterine ischemia due to excessive contractions triggered by increased endometrial prostaglandin release. Exercise-induced muscle contractions may enhance vascular circulation through muscle pump action, while also reducing pelvic muscle tension, improving blood flow, and facilitating clearance of nociceptive mediators.^27,28 Biochemical evidence indicates that exercise can modulate prostaglandin production, alter sex hormone levels, and lower systemic inflammatory cytokines.²⁹ In addition, central mechanisms such as β-endorphin release, activation of descending inhibitory pathways,³⁰ and reduced central sensitization contribute to exercise-induced analgesia.^30,31 Collectively, these mechanisms suggest that exercise alleviates menstrual pain through coordinated circulatory, biochemical, muscular, and neurophysiological effects. The findings of this study are consistent with previous evidence regarding the relationship between exercising with others and various health conditions.^15–20 However, the mechanism underlying the beneficial effect of exercising with others remains poorly understood. Exercise performed with others has been reported to be effective in alleviating depressive symptoms.¹⁵ Given the bidirectional association between menstrual pain and depression,³² exercising with others may help relieve menstrual pain by improving depressive symptoms. Menstrual pain might reduce the frequency of exercise and weaken the exercise intensity. Additionally, severe menstrual pain may result in avoidance of exercise with peers, partly due to consideration for their friends.

The present study has several limitations that should be noted. First, the cross-sectional study design does not permit the assessment of causality. Second, assessments of exercise habits, exercise partners, menstrual pain, medication, and menstrual regularity were based on nonvalidated self-administered questionnaires, which might have introduced some misclassification bias. Additionally, the weakness of study was a single self-reported measure of exercise habits. To understand the association between exercise habit and menstrual pain, we should use exercise diary or mobile application to assess exercise habit. Third, since health check-up data were used and no prior studies have investigated the association between exercise partners and menstrual pain, the required sample size could not be determined in advance. Fourth, potential confounding factors including stress, and lifestyle habits may not have been fully accounted for in this analysis. Additionally, we could not assess use of hormonal contraceptive, primary and secondary dysmenorrhea, and other medical conditions in this cohort. Finally, the study population may not be representative of all young Japanese women. Given that the present cohort consisted exclusively of university students, their relatively high educational status may have influenced health-related behaviors.

In conclusion, among young Japanese women, exercise frequency, intensity, and exercising with a partner were independently and inversely associated with menstrual pain. Further research is needed to explore the association between exercise habits and menstrual pain in order to improve patient care and enhance the quality of life for women.

Authors’ Contributions

J.W.: Conceptualization and writing—original draft and revised article. S.F.: Conceptualization, data curation, analysis, and writing—original draft and revised article. T.M.: Writing—review and editing. H.N.: Writing—review and editing. M.M.: Writing—review and editing. A.K.: Writing—review and editing. Y.M.: Writing—review and editing. O.Y.: Writing—review and editing. A.K.: Data curation. K.K.: Data curation. Y.H.: Supervision and project administration.

Footnotes

Acknowledgments

The authors would like to thank Shuichi Saheki, Yuka Saeki, Mikage Oiwa, Hiromi Miyauchi, Yuko Matsumoto, Miyuki Kataoka, Keiko Nakata, Hiroko Suzuki, Katsutoshi Okada, Katsuhiko Kohara, Masumi Hino, and Tomo Kogama for their support.

Author Disclosure Statement

The authors declare that they have no competing interests.

Funding Information

We declare that no financial support was received for the research, authorship, or publication of this article. The absence of funding was transparently disclosed, and none of the authors received any compensation. However, we acknowledge Ehime University for its contribution to data collection.

Data Availability

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Consent for Publication

Not applicable.

Supplemental Material

Abbreviations

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