Cardiovascular risk screening during mammography: high acceptability and potential equity gains

Background Cardiovascular (CV) disease is the leading cause of death among women, yet participation in CV risk assessment remains suboptimal. We developed a machine learning algorithm using routine mammographic features and age to predict CV risk in women. However, population acceptability, willingness to participate, and potential impact on screening behaviour remain unclear. This study explored women’s attitudes towards integrating CV risk screening into mammography. Methods We conducted a national cross-sectional web-based survey of Australian women aged ≥40 years recruited via registries and social media. The survey captured demographics, Socio-Economic Indexes for Areas (SEIFA), breast and CV screening history, and attitudes towards integrated CV screening. Logistic regression examined associations between participant characteristics and three outcomes: acceptability, willingness, and perceived impact on mammography attendance. Predictors included age, education, SEIFA, prior mammography, and prior CV risk assessment by a health professional. Results are reported as adjusted odds ratios (aORs) with 95% confidence intervals (CIs). Results Of 232 consented, 215 (93%) completed the survey. The largest age group was ≥65 years (39%). Respondents were predominantly university educated (60%), from higher SEIFA quintiles (Q4–5) (62%), and had previously undergone mammography (95%), with 82% attending every 1–2 years. In contrast, 55% had ever undergone CV risk assessment, with 43% attending every 1–2 years. Acceptability and willingness for mammography-based CV screening were near universal (98% and 99%); therefore, regression analyses focused on perceived impact on attendance. Most respondents (70%) perceived attendance would be more likely if CV screening were included. In adjusted analyses, women without university education had higher odds of reporting increased attendance compared with university-educated women (aOR 2.22, 95% CI 1.10–4.67, p=0.029). Women residing in socioeconomically disadvantaged areas had higher odds of perceived increased attendance, although this did not reach statistical significance (aOR 2.25, 95% CI 0.96–5.94, p=0.077). Age, prior mammography, and prior CV risk assessment were not associated. No subgroup anticipated reduced attendance. Preferred communication of results included digital delivery (81%) and/or direct communication to a general practitioner (46%). Interest in future research participation was high (95%). Conclusions Integrating CV risk screening into routine mammography is highly acceptable and may increase attendance. Education- and SEIFA-related differences suggest integrated screening may preferentially engage women currently underserved by existing CV prevention pathways, with potential to reduce socioeconomic inequalities in preventive care. Leveraging existing screening infrastructure represents a scalable, equity-enhancing strategy for population CV prevention in women.