Menopause in the All of Us Research Program: a descriptive summary of electronic health record and survey response across sociodemographic characteristics

Abstract

ABSTRACT Objective Menopause is a significant physiological transition with implications for health outcomes (e.g., cardiometabolic), yet gaps remain in understanding the menopause transition, including how menopause timing and type influence health outcomes. Large-scale cohort studies in midlife (age∼40-60) females, including the All of Us Research Program (AoURP), provide opportunities to study menopause across diverse populations and data modalities. We characterized menopause-related data in AoURP, focusing on age distributions and concordance between EHR diagnosis codes and self-reported survey responses. Methods We analyzed menopause-related survey, EHR diagnostic code, and genomic data among ∼396,000 participants in AoURP with female sex. We summarized menopause data across modalities, overlap between survey, EHR, and genomic data, and age distributions overall and across sociodemographic characteristics. Results Among ∼396,000 females, surveys captured ∼193,000 menopause observations, nearly seven times more than structured EHR diagnoses (∼28,000), suggesting under-ascertainement in EHR data. Nearly all females (∼99%) with an EHR menopause diagnosis also reported menopause in the survey. Approximately 22,000 participants had intersected EHR, survey, and genomic menopause-related data. Survey-based age patterns matched expectations, with participants <40 years predominantly reporting pre-menopausal status and those >60 years predominantly reporting post-menopausal status. A small subset (N≈1,700; 4%) (age>70 years) reported no menopause, suggesting response or recall bias. EHR menopause codes were concentrated after age>45 years, with a notable spike at age 65. Modest differences in survey-based menopause age distributions were observed by sociodemographic characteristics (e.g., race, ancestry). Conclusions These findings inform sampling strategies, power calculations, phenotype definition, and study design for menopause research using AoURP.