Systematic exclusion at study commencement masks earlier menopause for Black women in the Study of Women’s Health Across the Nation (SWAN)

Abstract

Abstract Background Shorter average lifespans for minoritized populations are hypothesized to stem from ‘weathering’ or accelerated health declines among minoritized individuals due to systemic marginalization. However, evidence is mixed on whether racial/ethnic differences exist in reproductive ageing, potentially due to selection biases in cohort studies that may systematically exclude ‘weathered’ participants. This study examines racial/ethnic disparities in the age of menopause after accounting for differential selection ‘into’ (left truncation) and ‘out of’ (right censoring) a cohort of midlife women. Methods Using data from the Study of Women’s Health Across the Nation (SWAN) cross-sectional screener (N = 15 695) and accompanying ∼20-year longitudinal cohort (N = 3302) (1995–2016), we adjusted for potential selection bias using inverse probability weighting (left truncation) to account for socio-demographic/health differences between the screening and cohort study, and multiple imputation (right censoring) to estimate racial/ethnic differences in age at menopause (natural and surgical). Results Unadjusted for selection, no Black/White differences in menopausal timing [hazard ratio (HR)=0.98 (0.86, 1.11)] were observed. After adjustment, Black women had an earlier natural [HR = 1.13 (1.00, 1.26)] and surgical [HR= 3.21 (2.80, 3.62)] menopause than White women with natural menopause—corresponding to a 1.2-year Black/White difference in menopause timing overall. Conclusions Failure to account for multiple forms of selection bias masked racial/ethnic disparities in the timing of menopause in SWAN. Results suggest that there may be racial differences in age at menopause and that selection particularly affected the estimated menopausal age for women who experienced earlier menopause. Cohorts should consider incorporating methods to account for all selection biases, including left truncation, as they impact our understanding of health in ‘weathered’ populations.