Menstrual Disorder Frequency Across Ibuprofen and Oral Contraceptive Treatment Modalities in Reproductive-Age Women: A Population-Based Analysis Using the NIH All of Us Research Program

Abstract

Introduction:

Despite the widespread use of nonsteroidal anti-inflammatory drugs and oral contraceptives (OC), population-level analyses on how menstrual disorder diagnoses vary across ibuprofen and OC use remain limited. Prior studies emphasize treatment efficacy for individual conditions rather than cross-sectional diagnosis co-occurrence across these treatment categories. The NIH All of Us Research Program enables age-stratified analyses of menstrual disorder diagnoses across ibuprofen and OC use.

Methods:

We conducted a retrospective cross-sectional analysis of female participants 18–35 years old using All of Us data from electronic health records, survey responses, and physical measurements. Participants were stratified into ages 18–24 and 25–35 years and grouped by recorded ibuprofen only, OC only, or ibuprofen + OC exposure. Standardized Observational Medical Outcomes Partnership concept sets identified dysmenorrhea, irregular menstruation, excessive/heavy bleeding, and amenorrhea. Pairwise chi-square tests compared diagnosis presence across treatment groups. The Holm–Bonferroni (HB) adjustment was applied. Treatment duration, dose, adherence, and temporal sequencing relative to diagnosis could not be established.

Results:

In women aged 18–24 years, no significant differences in diagnosis prevalence were observed between treatment groups (ibuprofen: n = 2832; OC: n = 4256; and combination: n = 2315). Between-group prevalence differences were modest (0.9 to 2.1 percentage points) and did not remain significant after HB correction (all HB adjusted p > 0.05). Women aged 25–35 years (ibuprofen: n = 9533; OC: n = 9517; and combination: n = 9617) had OC use associated with lower dysmenorrhea prevalence versus combination use (prevalence difference: 1.4%; HB-adjusted p < 0.05). Irregular menstruation was more frequent in the OC group than in the ibuprofen group (2.1%; HB-adjusted p < 0.05). Excessive/heavy bleeding was more prevalent with ibuprofen use than with OC use and combination therapy (2.2% and 1.6%, respectively; HB-adjusted p < 0.05). Amenorrhea prevalence did not differ significantly (≤0.9%; HB-adjusted p > 0.05).

Conclusions:

Menstrual disorder diagnosis frequencies differed across ibuprofen and OC exposure groups, primarily among women 25–35 years old. Longitudinal studies with untreated comparators and better characterizations of treatment timing, dose, and duration are needed.

Keywords

NSAIDS dysmenorrhea heavy menstrual bleeding amenorrhea irregular menses

Introduction

Menstrual pain, experienced as cramping in the lower abdomen and specifically painful menstrual periods, is clinically known as dysmenorrhea. It can significantly disrupt daily functioning, academic and occupational performance, and overall quality of life.^1,2 The reported prevalence of dysmenorrhea varies substantially across studies. Higher prevalence estimates are generally observed in younger women, ranging from 67% to 90% among those aged 17–24 years, with rates in 20–24 year old women reported between 15% and 75%.¹ Dysmenorrhea is typically classified as either primary (occurring without underlying pelvic pathology) or secondary (resulting from underlying pelvic conditions, i.e., endometriosis and fibroids), with primary dysmenorrhea being the most common form in younger individuals.³

Menstrual disorders encompass a broader spectrum beyond pain; irregular menstrual cycles are observed in up to 37% of young women aged 20–24 years, primarily due to ongoing maturation of the hypothalamic–pituitary–ovarian axis, and typically stabilize in later reproductive years, dropping to a prevalence of 25% by the age of 25–29 years.^4,5 Excessive and heavy menstrual bleeding affects up to 37% of adolescents and approximately 20% of adult women.^6,7 Amenorrhea (excluding pregnancy, lactation, and menopause) affects about 3%–4% of women in their reproductive years, the majority being secondary amenorrhea.^8,9 Additionally, women aged 25–35 years often exhibit distinct menstrual patterns, including changes in cycle regularity, bleeding volume, and pain severity influenced by reproductive histories, prolonged medication exposure, and a higher prevalence of underlying gynecological conditions, including endometriosis, uterine fibroids, and polycystic ovary syndrome (PCOS).^10–12

Nonsteroidal anti-inflammatory drugs (NSAIDs), such as ibuprofen, are recommended as a first-line treatment for dysmenorrhea because they inhibit prostaglandin production, which in turn reduces uterine contractions and menstrual pain.¹³ Using oral contraceptives (OCs) offers benefits by suppressing ovulation and stabilizing the uterine lining, not only relieving pain but also normalizing cycle length and reducing bleeding volume.¹⁴ The efficacy of NSAIDs and OCs as stand-alone treatments is well supported by multiple systematic reviews and clinical guidelines.^12,14–16

Despite the widespread use of NSAIDs and OCs, population-level characterization of menstrual disorder diagnoses within treatment-exposed cohorts remains limited. Most prior studies have focused on treatment efficacy for individual conditions or have taken a diagnosis-anchored approach. The present analysis was intentionally structured to define cohorts based on treatment exposure and to examine the distribution of menstrual disorder diagnoses within these groups, providing a complementary, treatment-centered perspective on real-world clinical patterns. This approach allows characterization of how menstrual disorder diagnoses are represented within commonly used pharmacologic strategies in a large, diverse population. This framework is intended to complement, rather than replace, traditional diagnosis-centered analyses.

Materials and Methods

Study design and objective

This retrospective cohort study utilized data from the NIH All of Us Research Program, a national precision medicine initiative developed to gather health information from individuals across diverse racial, ethnic, geographic, and socioeconomic backgrounds in the United States.¹⁷ All of Us data are harmonized to the Observational Medical Outcomes Partnership (OMOP) Common Data Model, enabling standardized identification of diagnoses and drug exposures through curated OMOP concept sets. Unlike clinical trials with limited populations, this data set provides an observational population-based dataset representation of menstrual health across a spectrum of demographic subgroups, thus enhancing the generalizability of findings evaluating multiple menstrual outcomes beyond dysmenorrhea.

Data processing

All data processing was conducted using Python 3.10 within the JupyterLab environment provided by the All of Us platform. Condition data were merged with demographic variables using unique identifiers.

Duplicate condition entries were removed to avoid inflating diagnosis counts. Diagnosis frequency distributions were then generated for each treatment group within each age category. Ibuprofen was selected as a representative NSAID due to its common use and consistent identification within the dataset; however, over-the-counter use may be incompletely captured in EHR-derived data unless documented during clinical encounters.

To account for physiological differences and distinct clinical characteristics, the data were stratified into two age groups: 18–24 and 25–35 years. Within each age stratum, the independent variable was treatment group (ibuprofen only, OC only, and combination), and the dependent variable was the presence (yes/no) of a given diagnosis (dysmenorrhea, irregular menstruation, excessive/frequent bleeding, or amenorrhea) at the person level. Concept sets were created to identify diagnoses related to dysmenorrhea, irregular menstruation, amenorrhea, and excessive or frequent bleeding. Concept sets are curated collections of standardized clinical codes (SNOMED-CT and ICD-10-CM) used within the OMOP Common Data Model corresponding to clinically recognized menstrual disorder categories (Supplementary Table). Amenorrhea concept sets included secondary amenorrhea diagnoses; physiological or pregnancy-related codes were excluded. Using the All of Us Dataset Builder, we created a total of six cohorts reflecting the three treatment types across the two age groups. A separate “Other” category included 15 less common menstrual conditions such as short cycles, prolonged menstruation, or cycle disorders not otherwise specified. This “Other” category was not included in the analysis due to small sample sizes. Treatment exposures and diagnoses were defined using any recorded occurrence in the dataset, without a fixed index date. Thus, variables reflect lifetime presence, and no temporal sequencing between treatment and diagnosis was established.

Dataset builder workflow

For each of the six cohorts, datasets were generated using a standardized workflow in the All of Us Researcher Workbench:

Cohort selection applied age range and gender (female) filters and selected drug exposure criteria corresponding to ibuprofen only, OC only, or both.

All of Us concept sets were used to identify relevant diagnoses without applying inclusion or exclusion filters.

Variable extraction included the following:

Demographic variables: person_id, gender, sex_at_birth, date_of_birth, race, and ethnicity.

Clinical condition variables: condition_concept_id, standard_concept_name,condition_start_datetime, and condition_type_concept_name.

Vocabulary/source terms: source_concept_name and source_vocabulary.

Medication data: drug_exposure_start_time when applicable.

This structured extraction ensured consistency across all datasets and preserved the reproducibility of cohort selection and variable definitions.

Statistical analysis

Within each age group, three pairwise treatment comparisons were made as follows: (1)

Ibuprofen versus OC.

(2)

Ibuprofen versus combination therapy.

(3)

OC versus combination therapy.

Because the NIH All of Us Research Workbench does not conduct inferential statistical testing, we evaluated associations between treatment group and diagnosis status within each age stratum and for each menstrual diagnosis using pairwise 2 × 2 chi-square tests of independence. Treatment groups were compared directly as follows: (1) OC use versus ibuprofen-only use, (2) OC use versus combined ibuprofen + OC use, and (3) ibuprofen-only use vs. combined ibuprofen + OC use.

For each comparison, the dependent variable was the presence or absence of the diagnosis (yes/no), and the independent variable was the treatment group. Two-sided p-values were reported using Pearson’s chi-square test with statistical significance defined as α = 0.05. Additionally, to account for multiple pairwise comparisons within each outcome and age stratum, Holm–Bonferroni (HB) correction was applied as a sensitivity adjustment across the three pairwise tests per outcome. Analysis of variance was not performed because all outcome variables were binary (diagnosis present vs. absent), making categorical association testing via chi-square the appropriate statistical approach.

Software and tools

Data merging and filtering were conducted using standard pandas operations, including pd.merge() for joining dataframes and conditional filtering for subgroup selection (e.g., restricting to female participants). For exploratory data analysis and visualization, the ydata_profiling package (formerly pandas_profiling) was used to generate summary statistics and profile reports within the All of Us Jupyter Notebook environment. All analyses were executed within this secure platform to ensure compliance with data privacy and reproducibility standards.

Results

Concept sets stratified by age were created to identify diagnoses related to dysmenorrhea, irregular menstruation, amenorrhea, and excessive or frequent bleeding (Table 1 and Table 2).

Table 1.

Menstrual Conditions by Treatment Group in Patients Aged 18–24 Years

Condition	Ibuprofen (n = 2832)	OC-only (n = 4256)	Ibuprofen + OC (n = 2315)
Dysmenorrhea	960	1533	811
Irregular periods	713	984	555
Excessive and frequent menstruation	279	444	213
Amenorrhea	294	404	240

Table 2.

Menstrual Conditions by Treatment Group in Patients Aged 25–35 Years

Condition	Ibuprofen (n = 9533)	OC-only (n = 9517)	Ibuprofen + OC (n = 9617)
Dysmenorrhea	1533	1419	1567
Irregular periods	2914	3109	3048
Excessive/Heavy bleeding	1138	922	993
Amenorrhea	2386	2353	2318

In the 18–24-year-old cohort (Fig. 1), the prevalence of dysmenorrhea ranged from 33.9% to 36.0%, irregular menstruation from 23.1% to 25.2%, excessive or heavy bleeding from 9.2% to 10.4%, and amenorrhea from 9.5% to 10.4% across treatment groups. Absolute between-group prevalence differences were modest (range: 0.9–2.1 percentage points). Following HB correction for multiple pairwise comparisons, no statistically significant differences were observed between ibuprofen-only, OC-only users, or combination users for any of the four menstrual outcomes (all Holm-adjusted p > 0.05).

FIG. 1.

Frequency of top four menstrual conditions with Holm–Bonferroni-adjusted pairwise p-values in 18–24-year-olds.

In the 25–35-year-old cohort (Fig. 2), greater between-group variation was observed. Dysmenorrhea prevalence was 16.1% in ibuprofen-only users, 14.9% in OC-only users, and 16.3% in combination users, corresponding to a 1.4 percentage-point lower prevalence in OC-only users compared with combination users (OC-only vs. combination, p = 0.0283). Irregular menstruation prevalence was 30.6% in ibuprofen-only users, 32.7% in OC-only users, and 31.7% in combination users, with the highest prevalence observed in OC-only users, reflecting a 2.1 percentage point higher prevalence than ibuprofen-only users (OC-only vs. ibuprofen only, p = 0.0058). Excessive/heavy bleeding prevalence was 11.9% in ibuprofen-only users, 9.7% in OC-only users, and 10.3% in combination users, representing absolute differences of 2.2 and 1.6 percentage points when compared with ibuprofen-only users (ibuprofen-only vs. OC-only, p < 0.0001; ibuprofen-only vs. combination, p = 0.008). Amenorrhea prevalence was similar across groups ranging from 24.4% to 25.0%, with all comparisons yielding p > 0.05.

FIG. 2.

Frequency of top four menstrual conditions with Holm-adjusted pairwise p-values in 25–35-year-olds.

Discussion

This describes patterns of menstrual disorder diagnoses among women with recorded ibuprofen and/or OC exposure in a large national dataset. Differences in diagnosis prevalence were more apparent in the 25–35 year cohort than in the 18–24 year cohort, where the younger participants demonstrated relatively similar prevalence estimates across all groups. These findings should be interpreted as descriptive associations rather than evidence of treatment effectiveness or causal relationships. Statistically significant differences in diagnosis frequencies associated with OC use emerged primarily in women aged 25–35 years. The patterns observed across the three treatment modalities suggest that therapeutic use may differ across menstrual disorders, meaning a treatment may be beneficial in one domain but less suitable in another.

Age-stratified analyses revealed distinct patterns across cohorts. In the 18–24 year-old cohort, diagnosis frequencies and symptom prevalence were similar across medication exposure groups following HB correction. The absence of statistically significant differences in this age group contrasts with patterns observed in older women and may reflect differences in baseline cycle variability, hormonal dynamics, or medication selection behaviors. These findings suggest that medication exposure differences may become more pronounced with increasing reproductive age.

In contrast, the 25–35 year-old cohort demonstrated clearer variation in menstrual diagnosis prevalence across medication exposure groups. Dysmenorrhea prevalence across medication exposure groups was lower than commonly reported population prevalence estimates.¹ This pattern may reflect differences in symptom burden, medication selection, or other underlying cohort characteristics across exposure groups. Prior studies have primarily emphasized NSAIDs as first-line therapy for dysmenorrhea and menorrhagia, focusing largely on symptom relief rather than broader modulation of menstrual patterns.^2,12,14,18 In our analysis, a lower prevalence of dysmenorrhea and heavy bleeding was seen with OC use only among women aged 25–35 years. Although differences in irregular menstruation did not reach statistical significance in younger women, frequencies were numerically lower among OC users compared with NSAID users. In women aged 25–35 years, combination ibuprofen–OC use was associated with lower rates of heavy bleeding compared with ibuprofen use only, though without additional benefit over OC use. Existing clinical guidelines have limited discussion of combined ibuprofen and OC use. Current clinical guidance from the American College of Obstetricians and Gynecologists continues to recommend initiating treatment with single agents, typically NSAIDs, or OC if contraception is also desired, prior to escalation to other hormonal approaches.^16,19,20 Similar recommendations are echoed in the recently published Society of Obstetricians and Gynaecologists of Canada Guideline Management and Oversight Committee.²¹ Our analysis indicates that single-agent therapy may warrant further prospective evaluation, particularly for patients with heavy or irregular bleeding, supporting an expanded role for hormonal therapies beyond contraception into broader menstrual regulation.²²

Consistent with this observation, reported irregular menstruations exceeded expected prevalence estimates for the 25–35 age group.^4,5 This elevation suggests that cycle variability remains a prominent clinical feature within this cohort.

OCs are commonly described as regulating cycles and reducing irregularity. In our analysis, older women using OC reported higher rates of irregular cycles compared with ibuprofen, which challenges the assumption that OC uniformly improve cycle regularity. This unexpected pattern suggests that in established cycles, OC-related breakthrough bleeding or variability during pill-free intervals may be perceived as irregularity, particularly in the presence of comorbid conditions such as PCOS, endometriosis, or fibroids. Recent work has highlighted the diagnostic and management challenges of endometriosis in primary care, underscoring the importance of accounting for comorbidities when interpreting menstrual cycle irregularity.²³

Published prevalence estimates for amenorrhea in reproductive-age women are generally around 3%–4%,^8,9 whereas our findings showed substantially higher rates in both younger and older women. This discrepancy may reflect differences between controlled study definitions and observational population-based dataset symptom reporting and highlights the limitations of studies that might use narrow clinical criteria.^24,25 Our results suggest that real-world reporting may capture a broader spectrum of absent menses, including skipped withdrawal bleeds, continuous OC use, or subclinical hormonal suppression, underscoring the need for more inclusive definitions in population research.

This study has several strengths that enhance its validity and clinical relevance. Leveraging the All of Us Research Program allowed access to a large, diverse, nationally representative population, enabling age-stratified cohort construction and standardized treatment categorization. The population-based design supports generalizability, and HB correction was applied as a conservative approach to multiple comparisons.

Importantly, this analysis is one of the first large-scale investigations examining real-world outcomes of combination (NSAID–OC) usage across multiple menstrual health indicators.

Certain limitations must be acknowledged. Reliance on self-reported symptom data introduces potential recall or reporting bias. Additionally, the analysis did not account for key confounding variables such as dosage, treatment duration, comorbidities, and adherence, which may influence observed associations. Because treatment and diagnosis were defined using any recorded occurrence, temporal sequencing could not be determined, and this cross-sectional design restricts causal inference. The absence of symptom severity or quality-of-life data limits insight into treatment impact on lived experiences, thus limiting interpretation to associations rather than causality. Because treatments were not randomly assigned, residual confounding by indication is likely, and cross-sectional timing allows reverse causation (symptoms prompting therapy). Using longitudinal “new user” cohorts with propensity score methods or marginal structural models could better address these biases. Additionally, statistical testing was limited to pairwise Pearson 2 × 2 chi-square comparisons rather than multivariable or omnibus models, which may limit the ability to detect higher-order interaction effects.

Further research should pursue longitudinal study designs capable of assessing sustained treatment effects over time. Dose–response analyses for both ibuprofen and OC would provide critical insights, as would integrating validated patient-reported outcome measures assessing symptom burden, satisfaction, and functional impairment. Further stratified analyses, incorporating variables such as PCOS, athletic activity levels, and mental health status, in addition to a patient’s age, could uncover differential treatment responsiveness and refine personalized therapeutic strategies.

Authors’ Contributions

Q.F. and M.A.A.E. conceived the project and contributed to conceptualization, methodology, formal analysis, visualization, and original draft preparation. P.W.Z. contributed to the conception of the project, article editing and review, and provided supervision. C.M.S. helped with article writing, editing, and review. All authors provided input during article preparation and approved the final version for publication.

Ethical Considerations

Not applicable. Data in the All of Us Research Program are deidentified, so additional IRB approval was not required.

Consent to Participate

Not applicable. Participants have consented to participate in research prior to inclusion in the All of Us database, so no further consent was required.

Consent for Publication

Not applicable. Participants have consented to participate in published research prior to inclusion in the All of Us database, so no further consent was required.

Data Availability

The data that support the findings of this study are available from the All of Us Research Program’s Controlled Tier Dataset v8, available to authorized users on the Research Workbench. https://www.researchallofus.org/data-tools/workbench/.

Supplemental Material

sj-docx-1-whr-10.1177_26884844261466539 — Supplemental material for Menstrual Disorder Frequency Across Ibuprofen and Oral Contraceptive Treatment Modalities in Reproductive-Age Women: A Population-Based Analysis Using the NIH All of Us Research Program

Supplemental material, sj-docx-1-whr-10.1177_26884844261466539 for Menstrual Disorder Frequency Across Ibuprofen and Oral Contraceptive Treatment Modalities in Reproductive-Age Women: A Population-Based Analysis Using the NIH All of Us Research Program by Quinn Fan, Mika Allyssa A. Esquillo, Christina M. Seeger, and Paul W. Zarutskie

Footnotes

Acknowledgment

The authors gratefully acknowledge All of Us participants for their contributions, without whom this research would not have been possible. We also thank the National Institutes of Health’s All of Us Research Program for making available the participant data and cohort examined in this study.

Author Disclosure Statement

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding Information

The authors received no financial support for the research, authorship, and/or publication of this article.

Abbreviations Used

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