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Baosen Meng

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Open access Aug 2026

Elevated cardiovascular risk associated with hormone replacement therapy: A comprehensive analysis of reproductive factors and atherosclerotic cardiovascular disease outcomes in the UK Biobank cohort

Abstract Introduction The cardiovascular effects of hormone replacement therapy (HRT) remain controversial. This study investigated HRT‐associated atherosclerotic cardiovascular disease (ASCVD) risk, focusing on reproductive characteristics. Material and Methods This prospective cohort study analyzed 170 250 women aged 40–69 years from UK Biobank (2006–2024). Cox proportional hazards regression models were employed to estimate ASCVD risk, with stratification by reproductive characteristics (age at menarche, age at menopause, and menopausal status) and age groups (≤45, 46–55, >55 years). Mediation analysis was conducted to examine potential biological pathways through sex hormones, inflammatory markers, and lipid profiles. All analyses were adjusted for demographic factors, socioeconomic status, lifestyle factors, and reproductive history. Results During follow‐up, 11 357 women (6.67%) developed ASCVD. HRT users demonstrated elevated ASCVD risk (adjusted HR 1.13, 95% CI 1.08–1.18, p < 0.001), primarily from increased ischemic stroke. Risk varied by reproductive characteristics: late menarche showed highest risk (HR 1.15, 95% CI 1.08–1.24), followed by late menopause (HR 1.25, 95% CI 1.01–1.54). Perimenopause demonstrated the most pronounced elevation (HR 1.28, 95% CI 1.12–1.46). Women ≤45 years had 77% higher ASCVD risk with HRT use. Dose–response relationships between HRT duration (≥5 years) and ASCVD risk were observed (p overall = 0.009, p nonlinear = 0.004). Mediation analysis revealed minimal indirect effects through traditional biomarkers (<2%), suggesting direct vascular mechanisms. Conclusions HRT increases ASCVD risk with substantial variation by reproductive characteristics. Findings support reproductive profile‐based cardiovascular risk assessment for personalized HRT prescribing.

Meng-Chun Wang, Can Zhang, Chunlai Yang et al. · 0 citations

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