Incident Rosacea and Related Dermatoses in Estrogen-Exposed Females: A Large-Scale Age-Stratified Cohort Study

Incident Rosacea and Related Dermatoses in Estrogen-Exposed Females: A Large-Scale Age-Stratified Cohort Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Incident Rosacea and Related Dermatoses in Estrogen-Exposed Females: A Large-Scale Age-Stratified Cohort Study Zainab Yousaf, Juliana Cantor, Daphne G. Eckembrecher, Ayezel Munoz Gonzalez This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8859614/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 9 You are reading this latest preprint version Abstract Background: Rosacea is a chronic inflammatory facial dermatosis that disproportionately affects women and may vary across hormonal life stages. Fluctuations in estrogen levels across the female lifespan, particularly during perimenopause and postmenopausal stages, have been hypothesized to contribute to the development of inflammatory, pigmentary, and androgen-mediated dermatologic conditions. However, population-level data evaluating the association between estrogen exposure and incident rosacea across hormonally defined life stages remain limited. This study assesses the association between exogenous estrogen exposure and incident rosacea and related dermatological conditions across premenopausal, perimenopausal, and postmenopausal women. Methods: A retrospective cohort study was conducted using the TriNetX Research Network. Female patients were stratified into premenopausal (< 44 years), perimenopausal (45–55 years), and postmenopausal (≥ 56 years) cohorts. Within each age stratum, estrogen-exposed patients, defined by documented estrogen-containing hormonal contraceptive use or hormone replacement therapy use, were propensity score-matched 1:1 to estrogen-unexposed controls. The primary outcome was incident rosacea (ICD-10 L71.x) within three years following the index event. Secondary outcomes included other/unspecified rosacea, perioral dermatitis, and rhinophyma. Time-to-event analyses were performed using Kaplan–Meier methods and Cox proportional hazards models. Results: After matching, cohorts included 742,051 premenopausal, 54,248 perimenopausal, and 378,572 postmenopausal women per exposure group. Across all age groups, estrogen exposure was associated with a significantly lower recorded incidence of rosacea. Hazard ratios (HR) were 0.75 (95% CI 0.72–0.78; log-rank p < 0.001) in premenopausal women, 0.77 (95% CI 0.69–0.85; p < 0.001) in perimenopausal women, and 0.67 (95% CI 0.65–0.70; p < 0.001) in postmenopausal women. Similar associations were observed for other rosacea subtypes, perioral dermatitis, and rhinophyma across cohorts. Conclusion: Exogenous estrogen exposure was consistently associated with a lower recorded incidence of rosacea and related inflammatory facial dermatoses across female hormonal life stages. These findings underscore the importance of hormonal context and diagnostic patterns in rosacea epidemiology and support further investigation into hormonal modulation of inflammatory skin disease. Dermatology Rosacea Estrogen Menopause Hormone Replacement Therapy Introduction Rosacea is a chronic inflammatory facial dermatosis characterized by persistent erythema, papules, pustules, and, in advanced cases, phymatous changes [1]. The disease disproportionately affects women and often presents or fluctuates during periods of hormonal transition. Prior studies have suggested a potential relationship between estrogen, particularly estradiol, and rosacea-related vascular and inflammatory pathways; however, population-level data evaluating rosacea outcomes across hormonally defined female life stages remain limited [1]. Methods To evaluate rosacea and related dermatologic outcomes in relation to estrogen exposure, we conducted a retrospective cohort study using the TriNetX Research Network, an electronic health record database, comprising data from 112 healthcare organizations. Female patients were stratified into three age-based cohorts reflecting menopausal status: premenopausal (<44 years), perimenopausal (45–55 years), and postmenopausal (≥56 years), consistent with published definitions [1,2]. Diagnoses were identified using the International Classification of Diseases, 10th Revision, Clinical Modification [ICD-10-CM], and medication exposures were identified using RxNorm, a standardized nomenclature for clinical drugs maintained by the United States National Library of Medicine [3]. Within each age stratum, two cohorts were created: estrogen-unexposed and estrogen-exposed patients. All patients were required to have documentation of a general medical examination [Z00] to ensure healthcare engagement. Exclusion criteria included pregnancy-related diagnoses [O00–O9A], menopausal or climacteric conditions [N95.1, Z78.0], postpartum care [Z39], surgical menopause [Z90.71, Z90.722], premature menopause [E28.31], liver disease [K70–K77], or any estrogen-related prescriptions or diagnoses. Estrogen exposure was defined by documented prescriptions or diagnostic codes indicating use of estrogen-containing therapies, including hormonal contraceptives or hormone replacement therapy [RxNorm codes 4100, 4099, 214549, 4083, 4124; ICD-10 Z79.3, Z92.23, Z79.890]. Differences in estrogen route of administration and treatment duration were not distinguishable within the dataset and were therefore analyzed as a composite exposure. Unexposed patients had no history of estrogen-related prescriptions or diagnoses. Results All cohorts were matched 1:1 using the greedy nearest-neighbor propensity score algorithm based on age at index, race, ethnicity, and baseline comorbidities, resulting in well-balanced final cohorts including 742,051 patients per group in the premenopausal cohort, 54,248 per group in the perimenopausal cohort, and 378,572 per group in the postmenopausal cohort (Table 1). The primary outcome of incident rosacea [L71] along with secondary dermatological conditions, including other/unspecified rosacea [L71.8, L71.9], perioral dermatitis [L71.0], acne [L70], rhinophyma [L71.1], and androgenic alopecia [L64], were analyzed within three years of the index event. The index event was defined as the first qualifying cohort-specific encounter, representing initiation of estrogen exposure in exposed patients and a general medical examination in unexposed controls. Patients with a documented diagnosis of the outcome before the index event were excluded from the respective analyses. Outcomes were performed using TriNetX-built-in tools, including absolute risk calculations, time-to-event analyses using Kaplan-Meier survival curves with log-rank testing, and hazard ratios using Cox proportional hazards models with 95% confidence intervals (CIs). Across all age-defined cohorts, estrogen exposure was associated with a significantly lower incidence of rosacea compared with matched unexposed controls (Table 2). In premenopausal women, estrogen exposure was associated with a reduced hazard of rosacea (HR 0.75; 95% CI 0.72–0.78; log-rank p<0.001). Similar associations were observed in perimenopausal women (HR 0.77; 95% CI 0.69–0.85; p<0.001), with the strongest association seen among postmenopausal women (HR 0.67; 95% CI 0.65–0.70; p<0.001). Secondary analyses demonstrated consistent findings with estrogen exposure associated with reduced hazards of other/unspecified rosacea, perioral dermatitis, and rhinophyma across all age groups, again with the strongest effects seen in postmenopausal patients (Table 3). Discussion & Conclusion These findings indicate a strong association between estrogen exposure and lower recorded incidence of rosacea and related inflammatory facial dermatoses across hormonally defined female life stages. Several factors may contribute to the observed associations. Patients receiving estrogen therapies may have more frequent clinical encounters, allowing for earlier identification and management of facial erythema or acneiform eruptions before progression to a rosacea diagnosis. [5] Additionally, diagnostic overlap between rosacea, menopausal flushing, acne, and perioral dermatitis, especially during periods of hormonal transition, may influence coding practices. The stronger associations observed in postmenopausal women may reflect both increased baseline rosacea risk in the population and greater diagnostic specificity once menopausal vasomotor symptoms stabilize.[5] Importantly, this study does not establish a causal or direct biological protective effect of estrogen on rosacea pathogenesis, and it does not necessarily contradict prior studies reporting that estradiol may exacerbate rosacea-related symptoms or inflammatory responses.[4-6] Our findings evaluate the risk of incident diagnosis over time and primarily reflect differences in disease recognition, diagnostic coding, or healthcare utilization patterns, rather than a direct protective biological effect of estrogen on rosacea pathogenesis. Limitations of this study include potential misclassification of estrogen exposure, inability to assess dosage or duration, and residual confounding inherent to retrospective database analyses. Additionally, menopausal status was approximated using age-based criteria, and important clinical variables such as rosacea severity, skin phototype, environmental triggers, and dermatologic treatment use were not available. Nonetheless, the use of strict cohort definitions, exclusion of prior outcomes, and propensity score matching strengthens the validity of these findings. These findings complement existing literature by addressing disease incidence rather than symptom severity and underscore the importance of considering hormonal context when evaluating rosacea risk. [6] Future studies are warranted to clarify the temporal and dose-dependent relationships between estrogen exposure and inflammatory facial dermatoses. Declarations Author contributions: ZY: Conceptualization; Methodology; Investigation; Data Curation; Writing—Original Draft; Writing—Review & Editing. DE: Methodology; Investigation; Data Curation; Writing—Review & Editing. JC: Conceptualization; Investigation, Writing—Review & Editing. AMG: Conceptualization; Methodology; Supervision; Writing—Review & Editing. Funding : None Data availability: The data to support this study are available on the TriNetX Analytics Network (https://trinetx.com). Conflicts of Interest:The authors declare no conflicts of interest. Study/IRB Approval: Not applicable Patient Consent: Not applicable References Yang F, Wang L, Jiang X (2024) Clinical characteristics of rosacea in perimenopausal women. Skin research and technology: official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI). 30(1):e13542. https://doi.org/10.1111/srt.13542 Peacock K, Carlson K, Ketvertis KM Menopause. [Updated 2023 Dec 21]. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2025 Jan-. Available from: https://www.ncbi.nlm.nih.gov/books/NBK507826/ Gliklich RE, Leavy MB Data Standards. In: Gliklich RE, Leavy MB, Dreyer NA, editors. Tools and Technologies for Registry Interoperability, Registries for Evaluating Patient Outcomes: A User’s Guide, 3rd Edition, Addendum 2 [Internet]. Rockville (MD): Agency for Healthcare Research and Quality (US); 2019 Oct. Table 3 – 1, Examples of vocabulary and terminology standards* Available from: https://www.ncbi.nlm.nih.gov/books/NBK551886/table/ch3.tab1/ Jin Tang P, Chen C, Huang W, Wang B, Wang W, Shi Y, Tang Z, Deng Y, Zhang J, Li D, Jian (2025) 17β-Estradiol promotes LL37-induced rosacea-like skin inflammation via G protein-coupled estrogen receptor 30. J Dermatol Sci 119(3):101–111 Wu W, Geng H, Cho E, Eliassen A, Drucker A, Li T, Qureshi A, Li W Reproductive and hormonal factors and risk of incident rosacea among US White women. J Am Acad Dermatol, 87, Issue 1, 138–140 Liu H, Zhang L, Yuan J, Liang J, Zhang Y, Gao Z, Chen Y, Wang Y, Li Y, Zeng W, Yang F (2026) Risk Factor Analysis Based on Disease Severity: Rosacea Disease Management Strategies and Personalized Recommendations. J Cosmet Dermatol 25(1):e70525. https://doi.org/10.1111/jocd.70525 Tables Table 1: “Baseline characteristics after propensity score matching” Cohort 1 (Unexposed) 2 (Exposed) Characteristic Premenopausal (n=742,051) Perimenopausal (n=54,248) Postmenopausal (n= 378,572) 1 2 Current Age, mean (SD), y 29.1 (8.3) 28.5 (8.2) 51.4 (2.9) 51.4 (2.9) 70.2 (9.0) 70.1 (9.1) 1 2 Age at Index, mean (SD), y 22.7 (8.3) 21.9 (75) 45.4 (4.8) 45.4 (5.1) 63.2 (10.0) 63.0 (10.0) 1 2 Race White, n (%) 475,191(64.0%) 521,842 (70.3%) 40,688 (75.0%) 40,289 (74.3%) 313,717 (82.9%) 314,226 (83.0% 1 2 Black or African American, n (%) 110,063 (14.8%) 91, 083 (12.3%) 6,163 (11.4%) 6,165 (11.4%) 26,523 (7.0%) 26,854 (7.1%) 1 2 Asian, n (%) 38,639 (5.2%) 28,966 (3.9%) 2,410 (4.4%) 2,629 (4.8%) 12,225 (3.2%) 12,271 (3.2%) 1 2 Ethnicity Hispanic or Latino, n (%) 84,013 (11.3%) 63,171 (8.5%) 4,183 (7.7%) 4,399 (8.1%) 14,262 (3.8%) 14,492 (3.8%) 1 2 Not Hispanic or Latino, n (%) 477,532 (64.4%) 502,030 (67.7%) 38,965 (71.8%) 38,258 (70.5%) 283,252 (74.8%) 281,421 (74.3%) Table 2: “Incident rosacea following estrogen exposure across female hormonal life stages” Age Group Cohorts (n) Rosacea outcomes Risk Risk difference p-value Hazard Ratio (95% CI) Log-Rank p-value Premenopausal (<44 years) Unexposed (n= 738,352) Exposed (n= 737,519) 3,532 5,118 0.005 0.007 =0.000 0.75 (0.719–0.783) =0.000 Perimenopausal (45–55 years) Unexposed (n= 53,189) Exposed (n= 52,755) 689 851 0.013 0.016 =0.000 0.767 (0.694-0.848) =0.000 Postmenopausal (≥56 years) Unexposed (n= 369,761) Exposed (n= 365,833) 3,942 5,753 0.011 0.016 =0.000 0.673 (0.647-0.701) =0.000 Table 3: “Rosacea-Related Dermatologic Outcomes Associated With Estrogen Exposure” Cohort 1- Unexposed 2- Exposed Outcome Age Group Patients (n) Outcomes Risk Risk difference p-value Hazard Ratio (95% CI) Log-Rank p-value 1 2 1 2 1 2 Other/Unspecified Rosacea Premenopausal Perimenopausal Postmenopausal 739,571 739,315 53,300 52,997 370,247 366,592 2,342 3,141 587 709 3,619 5,168 0.003 0.004 0.011 0.013 0.010 0.014 =0.000 =0.000 =0.000 0.811 (0.769-0.856) 0.787 (0.575-0.782) 0.689 (0.660-0.719) =0.000 =0.000 =0.000 1 2 1 2 1 2 Perioral Dermatitis Premenopausal Perimenopausal Postmenopausal 678,929 635,319 53,840 53,504 375,562 372,547 31,176 36,785 277 392 1,510 2,628 0.046 0.058 0.005 0.007 0.004 0.007 =0.000 =0.000 =0.000 0.854 (0.841-0.866) 0.671 (0.575-0.782) 0.566 (0.531-0.603) =0.000 =0.000 =0.000 1 2 1 2 1 2 Rhinophyma Premenopausal Perimenopausal Postmenopausal 739,982 738,985 53,972 53,782 376,151 373,461 2,012 3,247 147 220 1,075 1,903 0.003 0.004 0.003 0.004 0.003 0.005 =0.000 =0.000 =0.000 0.673 (0.637-0.712) 0.673 (0.517-0.785) 0.557 (0.517-0.600) =0.000 =0.000 =0.000 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: Revision requested 05 May, 2026 Reviews received at journal 02 Apr, 2026 Reviewers agreed at journal 25 Mar, 2026 Reviews received at journal 25 Mar, 2026 Reviewers agreed at journal 25 Mar, 2026 Reviewers invited by journal 24 Mar, 2026 Editor assigned by journal 14 Feb, 2026 Submission checks completed at journal 14 Feb, 2026 First submitted to journal 12 Feb, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8859614","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":612271045,"identity":"72ffbb64-3921-4882-9404-df1186499d3f","order_by":0,"name":"Zainab Yousaf","email":"","orcid":"","institution":"University of Texas Medical Branch, John Sealy School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Zainab","middleName":"","lastName":"Yousaf","suffix":""},{"id":612271046,"identity":"bf334d41-b52c-44bb-adc7-2471e5087a8c","order_by":1,"name":"Juliana Cantor","email":"","orcid":"","institution":"Universidad de Los Andes","correspondingAuthor":false,"prefix":"","firstName":"Juliana","middleName":"","lastName":"Cantor","suffix":""},{"id":612271052,"identity":"8540cc50-012a-4326-810b-404efffe9032","order_by":2,"name":"Daphne G. Eckembrecher","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAy0lEQVRIiWNgGAWjYDCCAwwMjA0MDAn8QDYzA4RDpBbJBmZStRgcIFYL3/nFBz/OqNiWZ3wj/+jmAgYb2Q0HCGiRvPEsWXLDmdvFZjeS2W7PYEgzJqjF4MYZM8aHbbcTt4G08DAcTiRCy/lvjA//3U7cPAOs5T8RWs73sDFubLiduEECrOUAYS2SN9iMJWccu10sceax2e0ZBsnGMwlp4Tt/+OHHnprbefztic9uF1TYyfYR0sIgkYDiTkLKQYCfoKGjYBSMglEw4gEAXBlQzBfOx/QAAAAASUVORK5CYII=","orcid":"","institution":"The University of Texas Medical Branch at Galveston","correspondingAuthor":true,"prefix":"","firstName":"Daphne","middleName":"G.","lastName":"Eckembrecher","suffix":""},{"id":612271056,"identity":"b6b49d97-b842-4bbb-8ba0-38382e1a937f","order_by":3,"name":"Ayezel Munoz Gonzalez","email":"","orcid":"","institution":"The University of Texas Medical Branch at Galveston","correspondingAuthor":false,"prefix":"","firstName":"Ayezel","middleName":"Munoz","lastName":"Gonzalez","suffix":""}],"badges":[],"createdAt":"2026-02-12 08:38:42","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8859614/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8859614/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":105469343,"identity":"7b0a06d0-0888-4efa-8dcd-0fe2c7f12217","added_by":"auto","created_at":"2026-03-26 11:27:24","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":529866,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8859614/v1/7885d44a-f7d0-4f6a-b4db-c61690ad1086.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Incident Rosacea and Related Dermatoses in Estrogen-Exposed Females: A Large-Scale Age-Stratified Cohort Study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eRosacea is a chronic inflammatory facial dermatosis characterized by persistent erythema, papules, pustules, and, in advanced cases, phymatous changes [1]. The disease disproportionately affects women and often presents or fluctuates during periods of hormonal transition. Prior studies have suggested a potential relationship between estrogen, particularly estradiol, and rosacea-related vascular and inflammatory pathways; however, population-level data evaluating rosacea outcomes across hormonally defined female life stages remain limited [1].\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eTo evaluate rosacea and related dermatologic outcomes in relation to estrogen exposure, we conducted a retrospective cohort study using the TriNetX Research Network, an electronic health record database, comprising data from 112 healthcare organizations. Female patients were stratified into three age-based cohorts reflecting menopausal status: premenopausal (\u0026lt;44 years), perimenopausal (45\u0026ndash;55 years), and postmenopausal (\u0026ge;56 years), consistent with published definitions [1,2]. Diagnoses were identified using the International Classification of Diseases, 10th Revision, Clinical Modification [ICD-10-CM], and medication exposures were identified using RxNorm, a standardized nomenclature for clinical drugs maintained by the United States National Library of Medicine [3].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWithin each age stratum, two cohorts were created: estrogen-unexposed and estrogen-exposed patients. All patients were required to have documentation of a general medical examination [Z00] to ensure healthcare engagement. Exclusion criteria included pregnancy-related diagnoses [O00\u0026ndash;O9A], menopausal or climacteric conditions [N95.1, Z78.0], postpartum care [Z39], surgical menopause [Z90.71, Z90.722], premature menopause [E28.31], liver disease [K70\u0026ndash;K77], or any estrogen-related prescriptions or diagnoses. Estrogen exposure was defined by documented prescriptions or diagnostic codes indicating use of estrogen-containing therapies, including hormonal contraceptives or hormone replacement therapy [RxNorm codes 4100, 4099, 214549, 4083, 4124; ICD-10 Z79.3, Z92.23, Z79.890]. Differences in estrogen route of administration and treatment duration were not distinguishable within the dataset and were therefore analyzed as a composite exposure. Unexposed patients had no history of estrogen-related prescriptions or diagnoses.\u0026nbsp;\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eAll cohorts were matched 1:1 using the greedy nearest-neighbor propensity score algorithm based on age at index, race, ethnicity, and baseline comorbidities, resulting in well-balanced final cohorts including 742,051 patients per group in the premenopausal cohort, 54,248 per group in the perimenopausal cohort, and 378,572 per group in the postmenopausal cohort (Table 1). The primary outcome of incident rosacea [L71] along with secondary dermatological conditions, including other/unspecified rosacea [L71.8, L71.9], perioral dermatitis [L71.0], acne [L70], rhinophyma [L71.1], and androgenic alopecia [L64], were analyzed within three years of the index event. The index event was defined as the first qualifying cohort-specific encounter, representing initiation of estrogen exposure in exposed patients and a general medical examination in unexposed controls. Patients with a documented diagnosis of the outcome before the index event were excluded from the respective analyses.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOutcomes were performed using TriNetX-built-in tools, including absolute risk calculations, time-to-event analyses using Kaplan-Meier survival curves with log-rank testing, and hazard ratios using Cox proportional hazards models with 95% confidence intervals (CIs). Across all age-defined cohorts, estrogen exposure was associated with a significantly lower incidence of rosacea compared with matched unexposed controls (Table 2). In premenopausal women, estrogen exposure was associated with a reduced hazard of rosacea (HR 0.75; 95% CI 0.72\u0026ndash;0.78; log-rank p\u0026lt;0.001). Similar associations were observed in perimenopausal women (HR 0.77; 95% CI 0.69\u0026ndash;0.85; p\u0026lt;0.001), with the strongest association seen among postmenopausal women (HR 0.67; 95% CI 0.65\u0026ndash;0.70; p\u0026lt;0.001). Secondary analyses demonstrated consistent findings with estrogen exposure associated with reduced hazards of other/unspecified rosacea, perioral dermatitis, and rhinophyma across all age groups, again with the strongest effects seen in postmenopausal patients (Table 3).\u003c/p\u003e"},{"header":"Discussion \u0026 Conclusion","content":"\u003cp\u003eThese findings indicate a strong association between estrogen exposure and lower recorded incidence of rosacea and related inflammatory facial dermatoses across hormonally defined female life stages.\u0026nbsp;Several factors may contribute to the observed associations. Patients receiving estrogen therapies may have more frequent clinical encounters, allowing for earlier identification and management of facial erythema or acneiform eruptions before progression to a rosacea diagnosis. [5] Additionally, diagnostic overlap between rosacea, menopausal flushing, acne, and perioral dermatitis, especially during periods of hormonal transition, may influence coding practices. The stronger associations observed in postmenopausal women may reflect both increased baseline rosacea risk in the population and greater diagnostic specificity once menopausal vasomotor symptoms stabilize.[5] Importantly, this study does not establish a causal or direct biological protective effect of estrogen on rosacea pathogenesis, and it does not necessarily contradict prior studies reporting that estradiol may exacerbate rosacea-related symptoms or inflammatory responses.[4-6]\u0026nbsp;Our findings evaluate the risk of incident diagnosis over time and primarily reflect differences in disease recognition, diagnostic coding, or healthcare utilization patterns, rather than a direct protective biological effect of estrogen on rosacea pathogenesis. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eLimitations of this study include potential misclassification of estrogen exposure, inability to assess dosage or duration, and residual confounding inherent to retrospective database analyses. Additionally, menopausal status was approximated using age-based criteria, and important clinical variables such as rosacea severity, skin phototype, environmental triggers, and dermatologic treatment use were not available. Nonetheless, the use of strict cohort definitions, exclusion of prior outcomes, and propensity score matching strengthens the validity of these findings. \u0026nbsp;These findings complement existing literature by addressing disease incidence rather than symptom severity and underscore the importance of considering hormonal context when evaluating rosacea risk. [6] Future studies are warranted to clarify the temporal and dose-dependent relationships between estrogen exposure and inflammatory facial dermatoses.\u0026nbsp;\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor contributions:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eZY: Conceptualization; Methodology; Investigation; Data Curation; Writing\u0026mdash;Original Draft; Writing\u0026mdash;Review \u0026amp; Editing.\u003c/p\u003e\n\u003cp\u003eDE: Methodology; Investigation; Data Curation; Writing\u0026mdash;Review \u0026amp; Editing.\u003c/p\u003e\n\u003cp\u003eJC: Conceptualization; Investigation, Writing\u0026mdash;Review \u0026amp; Editing.\u003c/p\u003e\n\u003cp\u003eAMG: Conceptualization; Methodology; Supervision; Writing\u0026mdash;Review \u0026amp; Editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e: None\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data to support this study are available on the TriNetX Analytics Network (https://trinetx.com).\u003c/p\u003e\n\u003cp\u003eConflicts of Interest:The authors declare no conflicts of interest.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eStudy/IRB Approval: Not applicable\u003c/p\u003e\n\u003cp\u003ePatient Consent: Not applicable\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eYang F, Wang L, Jiang X (2024) Clinical characteristics of rosacea in perimenopausal women. Skin research and technology: official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI). 30(1):e13542. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/srt.13542\u003c/span\u003e\u003cspan address=\"10.1111/srt.13542\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePeacock K, Carlson K, Ketvertis KM Menopause. [Updated 2023 Dec 21]. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2025 Jan-. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ncbi.nlm.nih.gov/books/NBK507826/\u003c/span\u003e\u003cspan address=\"https://www.ncbi.nlm.nih.gov/books/NBK507826/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGliklich RE, Leavy MB Data Standards. In: Gliklich RE, Leavy MB, Dreyer NA, editors. Tools and Technologies for Registry Interoperability, Registries for Evaluating Patient Outcomes: A User\u0026rsquo;s Guide, 3rd Edition, Addendum 2 [Internet]. Rockville (MD): Agency for Healthcare Research and Quality (US); 2019 Oct. Table 3\u0026thinsp;\u0026ndash;\u0026thinsp;1, Examples of vocabulary and terminology standards* Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ncbi.nlm.nih.gov/books/NBK551886/table/ch3.tab1/\u003c/span\u003e\u003cspan address=\"https://www.ncbi.nlm.nih.gov/books/NBK551886/table/ch3.tab1/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJin Tang P, Chen C, Huang W, Wang B, Wang W, Shi Y, Tang Z, Deng Y, Zhang J, Li D, Jian (2025) 17β-Estradiol promotes LL37-induced rosacea-like skin inflammation via G protein-coupled estrogen receptor 30. J Dermatol Sci 119(3):101\u0026ndash;111\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWu W, Geng H, Cho E, Eliassen A, Drucker A, Li T, Qureshi A, Li W Reproductive and hormonal factors and risk of incident rosacea among US White women. J Am Acad Dermatol, 87, Issue 1, 138\u0026ndash;140\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu H, Zhang L, Yuan J, Liang J, Zhang Y, Gao Z, Chen Y, Wang Y, Li Y, Zeng W, Yang F (2026) Risk Factor Analysis Based on Disease Severity: Rosacea Disease Management Strategies and Personalized Recommendations. J Cosmet Dermatol 25(1):e70525. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/jocd.70525\u003c/span\u003e\u003cspan address=\"10.1111/jocd.70525\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1:\u0026nbsp;\u003c/strong\u003e\u0026ldquo;Baseline characteristics after propensity score matching\u0026rdquo;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"708\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 13.2768%;\"\u003e\n \u003cp\u003eCohort\u003c/p\u003e\n \u003cp\u003e1 (Unexposed)\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2 (Exposed)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 35.8757%;\"\u003e\n \u003cp\u003eCharacteristic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.9492%;\"\u003e\n \u003cp\u003ePremenopausal (n=742,051)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.1017%;\"\u003e\n \u003cp\u003ePerimenopausal\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(n=54,248)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.7966%;\"\u003e\n \u003cp\u003ePostmenopausal\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(n= 378,572)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 13.2768%;\"\u003e\n \u003cp\u003e1 \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 35.8757%;\"\u003e\n \u003cp\u003eCurrent Age, mean (SD), y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.9492%;\"\u003e\n \u003cp\u003e29.1 (8.3)\u003c/p\u003e\n \u003cp\u003e28.5 (8.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.1017%;\"\u003e\n \u003cp\u003e51.4 (2.9)\u003c/p\u003e\n \u003cp\u003e51.4 (2.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.7966%;\"\u003e\n \u003cp\u003e70.2 (9.0)\u003c/p\u003e\n \u003cp\u003e70.1 (9.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 13.2768%;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 35.8757%;\"\u003e\n \u003cp\u003eAge at Index, mean (SD), y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.9492%;\"\u003e\n \u003cp\u003e22.7 (8.3)\u003c/p\u003e\n \u003cp\u003e21.9 (75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.1017%;\"\u003e\n \u003cp\u003e45.4 (4.8)\u003c/p\u003e\n \u003cp\u003e45.4 (5.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.7966%;\"\u003e\n \u003cp\u003e63.2 (10.0)\u003c/p\u003e\n \u003cp\u003e63.0 (10.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 13.2768%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 35.8757%;\"\u003e\n \u003cp\u003eRace\u003c/p\u003e\n \u003cp\u003eWhite, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.9492%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e475,191(64.0%)\u003c/p\u003e\n \u003cp\u003e521,842 (70.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.1017%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e40,688 (75.0%)\u003c/p\u003e\n \u003cp\u003e40,289 (74.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.7966%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e313,717 (82.9%)\u003c/p\u003e\n \u003cp\u003e314,226 (83.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 13.2768%;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 35.8757%;\"\u003e\n \u003cp\u003eBlack or African American, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.9492%;\"\u003e\n \u003cp\u003e110,063 (14.8%)\u003c/p\u003e\n \u003cp\u003e91, 083 (12.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.1017%;\"\u003e\n \u003cp\u003e6,163 (11.4%)\u003c/p\u003e\n \u003cp\u003e6,165 (11.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.7966%;\"\u003e\n \u003cp\u003e26,523 (7.0%)\u003c/p\u003e\n \u003cp\u003e26,854 (7.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 13.2768%;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 35.8757%;\"\u003e\n \u003cp\u003eAsian, n (%)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.9492%;\"\u003e\n \u003cp\u003e38,639 (5.2%)\u003c/p\u003e\n \u003cp\u003e28,966 (3.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.1017%;\"\u003e\n \u003cp\u003e2,410 (4.4%)\u003c/p\u003e\n \u003cp\u003e2,629 (4.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.7966%;\"\u003e\n \u003cp\u003e12,225 (3.2%)\u003c/p\u003e\n \u003cp\u003e12,271 (3.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 13.2768%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 35.8757%;\"\u003e\n \u003cp\u003eEthnicity\u003c/p\u003e\n \u003cp\u003eHispanic or Latino, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.9492%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e84,013 (11.3%)\u003c/p\u003e\n \u003cp\u003e63,171 (8.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.1017%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e4,183 (7.7%)\u003c/p\u003e\n \u003cp\u003e4,399 (8.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.7966%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e14,262 (3.8%)\u003c/p\u003e\n \u003cp\u003e14,492 (3.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 13.2768%;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 35.8757%;\"\u003e\n \u003cp\u003eNot Hispanic or Latino, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.9492%;\"\u003e\n \u003cp\u003e477,532 (64.4%)\u003c/p\u003e\n \u003cp\u003e502,030 (67.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.1017%;\"\u003e\n \u003cp\u003e38,965 (71.8%)\u003c/p\u003e\n \u003cp\u003e38,258 (70.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.7966%;\"\u003e\n \u003cp\u003e283,252 (74.8%)\u003c/p\u003e\n \u003cp\u003e281,421 (74.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2:\u003c/strong\u003e \u0026ldquo;Incident rosacea following estrogen exposure across female hormonal life stages\u0026rdquo; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"695\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33.5252%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge Group\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eCohorts (n)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.518%;\"\u003e\n \u003cp\u003eRosacea outcomes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.48921%;\"\u003e\n \u003cp\u003eRisk\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.3885%;\"\u003e\n \u003cp\u003eRisk difference\u003c/p\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.8561%;\"\u003e\n \u003cp\u003eHazard Ratio (95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.223%;\"\u003e\n \u003cp\u003eLog-Rank p-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33.5252%;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePremenopausal (\u0026lt;44 years)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eUnexposed (n= 738,352)\u003c/p\u003e\n \u003cp\u003eExposed (n= 737,519)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.518%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e3,532\u003c/p\u003e\n \u003cp\u003e5,118\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.48921%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.3885%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e=0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.8561%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.75 (0.719\u0026ndash;0.783)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.223%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e=0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33.5252%;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePerimenopausal (45\u0026ndash;55 years)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eUnexposed (n= 53,189)\u003c/p\u003e\n \u003cp\u003eExposed (n= 52,755)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.518%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e689\u003c/p\u003e\n \u003cp\u003e851\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.48921%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.013\u003c/p\u003e\n \u003cp\u003e0.016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.3885%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e=0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.8561%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.767 (0.694-0.848)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.223%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e=0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33.5252%;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePostmenopausal (\u0026ge;56 years)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eUnexposed (n= 369,761)\u003c/p\u003e\n \u003cp\u003eExposed (n= 365,833)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12.518%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e3,942\u003c/p\u003e\n \u003cp\u003e5,753\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.48921%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.011\u003c/p\u003e\n \u003cp\u003e0.016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.3885%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e=0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.8561%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.673 (0.647-0.701)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.223%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e=0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3:\u003c/strong\u003e \u0026ldquo;Rosacea-Related Dermatologic Outcomes Associated With Estrogen Exposure\u0026rdquo;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"711\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 13.0802%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCohort\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e1- Unexposed\u003c/p\u003e\n \u003cp\u003e2- Exposed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.6287%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOutcome\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eAge Group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9705%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003ePatients (n)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.1266%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eOutcomes\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6.75105%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRisk\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.1266%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRisk difference\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;p-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8776%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eHazard Ratio\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.43882%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eLog-Rank p-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 13.0802%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.6287%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOther/Unspecified Rosacea\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003ePremenopausal\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003ePerimenopausal\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003ePostmenopausal\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9705%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e739,571\u003c/p\u003e\n \u003cp\u003e739,315\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e53,300\u003c/p\u003e\n \u003cp\u003e52,997\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e370,247\u003c/p\u003e\n \u003cp\u003e366,592\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.1266%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2,342\u003c/p\u003e\n \u003cp\u003e3,141\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e587\u003c/p\u003e\n \u003cp\u003e709\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e3,619\u003c/p\u003e\n \u003cp\u003e5,168\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6.75105%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.011\u003c/p\u003e\n \u003cp\u003e0.013\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.010\u003c/p\u003e\n \u003cp\u003e0.014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.1266%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e=0.000\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e=0.000\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e=0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8776%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.811 (0.769-0.856)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.787 (0.575-0.782)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.689 (0.660-0.719)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.43882%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e=0.000\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e=0.000\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e=0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 13.0802%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.6287%;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePerioral Dermatitis\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003ePremenopausal\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003ePerimenopausal\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003ePostmenopausal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9705%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e678,929\u003c/p\u003e\n \u003cp\u003e635,319\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e53,840\u003c/p\u003e\n \u003cp\u003e53,504\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e375,562\u003c/p\u003e\n \u003cp\u003e372,547\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.1266%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e31,176\u003c/p\u003e\n \u003cp\u003e36,785\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e277\u003c/p\u003e\n \u003cp\u003e392\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1,510\u003c/p\u003e\n \u003cp\u003e2,628\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6.75105%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.046\u003c/p\u003e\n \u003cp\u003e0.058\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.1266%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e=0.000\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e=0.000\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e=0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8776%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.854 (0.841-0.866)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.671 (0.575-0.782)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.566 (0.531-0.603)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.43882%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e=0.000\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e=0.000\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e=0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 13.0802%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.6287%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRhinophyma\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003ePremenopausal\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003ePerimenopausal\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003ePostmenopausal\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.9705%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e739,982\u003c/p\u003e\n \u003cp\u003e738,985\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e53,972\u003c/p\u003e\n \u003cp\u003e53,782\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e376,151\u003c/p\u003e\n \u003cp\u003e373,461\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.1266%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2,012\u003c/p\u003e\n \u003cp\u003e3,247\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e147\u003c/p\u003e\n \u003cp\u003e220\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1,075\u003c/p\u003e\n \u003cp\u003e1,903\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6.75105%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.1266%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e=0.000\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e=0.000\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e=0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.8776%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.673 (0.637-0.712)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.673 (0.517-0.785)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.557 (0.517-0.600)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8.43882%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e=0.000\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e=0.000\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e=0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"archives-of-dermatological-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Archives of Dermatological Research](https://www.springer.com/journal/403)","snPcode":"403","submissionUrl":"https://submission.nature.com/new-submission/403/3","title":"Archives of Dermatological Research","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Dermatology, Rosacea, Estrogen, Menopause, Hormone Replacement Therapy","lastPublishedDoi":"10.21203/rs.3.rs-8859614/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8859614/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground:\u003c/h2\u003e \u003cp\u003eRosacea is a chronic inflammatory facial dermatosis that disproportionately affects women and may vary across hormonal life stages. Fluctuations in estrogen levels across the female lifespan, particularly during perimenopause and postmenopausal stages, have been hypothesized to contribute to the development of inflammatory, pigmentary, and androgen-mediated dermatologic conditions. However, population-level data evaluating the association between estrogen exposure and incident rosacea across hormonally defined life stages remain limited. This study assesses the association between exogenous estrogen exposure and incident rosacea and related dermatological conditions across premenopausal, perimenopausal, and postmenopausal women.\u003c/p\u003e\u003ch2\u003eMethods:\u003c/h2\u003e \u003cp\u003eA retrospective cohort study was conducted using the TriNetX Research Network. Female patients were stratified into premenopausal (\u0026lt;\u0026thinsp;44 years), perimenopausal (45\u0026ndash;55 years), and postmenopausal (\u0026ge;\u0026thinsp;56 years) cohorts. Within each age stratum, estrogen-exposed patients, defined by documented estrogen-containing hormonal contraceptive use or hormone replacement therapy use, were propensity score-matched 1:1 to estrogen-unexposed controls. The primary outcome was incident rosacea (ICD-10 L71.x) within three years following the index event. Secondary outcomes included other/unspecified rosacea, perioral dermatitis, and rhinophyma. Time-to-event analyses were performed using Kaplan\u0026ndash;Meier methods and Cox proportional hazards models.\u003c/p\u003e\u003ch2\u003eResults:\u003c/h2\u003e \u003cp\u003eAfter matching, cohorts included 742,051 premenopausal, 54,248 perimenopausal, and 378,572 postmenopausal women per exposure group. Across all age groups, estrogen exposure was associated with a significantly lower recorded incidence of rosacea. Hazard ratios (HR) were 0.75 (95% CI 0.72\u0026ndash;0.78; log-rank p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) in premenopausal women, 0.77 (95% CI 0.69\u0026ndash;0.85; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) in perimenopausal women, and 0.67 (95% CI 0.65\u0026ndash;0.70; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) in postmenopausal women. Similar associations were observed for other rosacea subtypes, perioral dermatitis, and rhinophyma across cohorts.\u003c/p\u003e\u003ch2\u003eConclusion:\u003c/h2\u003e \u003cp\u003eExogenous estrogen exposure was consistently associated with a lower recorded incidence of rosacea and related inflammatory facial dermatoses across female hormonal life stages. These findings underscore the importance of hormonal context and diagnostic patterns in rosacea epidemiology and support further investigation into hormonal modulation of inflammatory skin disease.\u003c/p\u003e","manuscriptTitle":"Incident Rosacea and Related Dermatoses in Estrogen-Exposed Females: A Large-Scale Age-Stratified Cohort Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-26 11:26:29","doi":"10.21203/rs.3.rs-8859614/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-05-05T21:11:04+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-02T17:33:58+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"256920888136407460388818879035349536898","date":"2026-03-25T21:56:14+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-25T15:06:23+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"295866919404597259780430420316796463746","date":"2026-03-25T14:27:26+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-03-25T02:11:43+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-02-14T06:25:38+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-02-14T06:23:40+00:00","index":"","fulltext":""},{"type":"submitted","content":"Archives of Dermatological Research","date":"2026-02-12T08:34:33+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"archives-of-dermatological-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Archives of Dermatological Research](https://www.springer.com/journal/403)","snPcode":"403","submissionUrl":"https://submission.nature.com/new-submission/403/3","title":"Archives of Dermatological Research","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"d7665224-aced-4613-9c4b-ec37f021f30f","owner":[],"postedDate":"March 26th, 2026","published":true,"recentEditorialEvents":[{"type":"decision","content":"Revision requested","date":"2026-05-05T21:11:04+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"in-revision","subjectAreas":[],"tags":[],"updatedAt":"2026-05-05T21:24:03+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-26 11:26:29","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8859614","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8859614","identity":"rs-8859614","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}