Health & Medicinearticle2026-09-22

Evaluating menopausal symptom burden and treatment engagement in a predominantly Hispanic population on the United States‐Mexico border

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Abstract

Objective: To evaluate menopausal symptom burden, health care engagement, and treatment disparities among postmenopausal women at the United States‐Mexico border. Methods: A cross-sectional bilingual survey was administered to postmenopausal women receiving care from 2021 to 2024 at a tertiary care center. Menopausal symptoms, treatment use, and health care clinician engagement were assessed. Associations were evaluated using multivariable logistic or Poisson regression. Results: Among 340 postmenopausal participants (mean age: 55.8 ± 7.0 y), the most frequently reported symptoms were sleep disturbances (73%; 95% CI: 68%-77%) and weight gain (68%; 95% CI: 63%-73%). Despite this high symptom burden, 58% (95% CI: 52%-63%) reported that their symptoms had never been addressed by a clinician. Younger participants (<55 y) had higher odds of vasomotor, sleep, and mood symptoms (all P <0.01), while older participants were more likely to have discussed menopause with a clinician (adjusted odds ratio [aOR] 1.86; 95% CI: 1.16-2.97, P = 0.01) or used hormone therapy (aOR 2.91; 95% CI: 1.53-5.50, P = 0.001). Higher education was associated with hormone therapy use (aOR: 5.63; 95% CI: 1.09-29.08; P = 0.039) and mental health treatment (aOR: 4.11; 95% CI: 1.30-13.02; P = 0.016). Despite similar symptom prevalence, Hispanic participants were less likely to have received mental health treatment (aOR: 0.35; 95% CI: 0.19-0.65; P = 0.001). Conclusions: Menopausal symptoms were common in this border-region cohort, yet clinician engagement and treatment use were low. Socioeconomic and ethnic disparities in treatment highlight the need for culturally and linguistically tailored menopause care.

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View paper (DOI)OpenAlexMenopause The Journal of The North American Menopause SocietyPublished 2026-09-22

Authors: Amber L. McFerren, Kelcy Steffen-Gutierrez, Sarah Johnson, Alok Dwivedi, Katelyn Welshans, Sireesha Y. Reddy

Institutions: Institute for Medical Informatics and Biostatistics, Texas Tech University, Texas Tech University Health Sciences Center