Gender-sensitive modelling of atherosclerosis among women in Portugal, 2025-2034

Background

Cardiovascular disease remains a leading cause of mortality among women and a major contributor to the burden of non-communicable diseases. Prevention and care pathways still insufficiently address sex- and gender-specific risk profiles. Evidence shows differences in risk factors, comorbidities, management and outcomes between women and men, supporting gender-sensitive policy modelling.

Methods

We applied the ATHEROS algorithm, a Bayesian epidemiological model of atherosclerosis, to estimate the impact of public health policies among women in Portugal (2025-2034). The model simulates 12 interventions across prevention, diagnosis, treatment and linkage to care. Three scenarios were analyzed: current, maximal and minimal implementation. Outcomes included risk factor prevalence, healthcare use and economic burden.

Results

Under current implementation, women’s risk profiles worsen by 2034 vs 2025, with hypertension (+1.8 pp), diabetes (+0.8 pp) and hypercholesterolemia (+2.7 pp), despite reduced smoking (-1.1 pp). Healthcare use increases (+1,611 hospitalizations; +10,964 emergency visits; +16,405 primary care consultations). Costs rise across all domains, including EUR63.0 million due to labor non-participation. Maximal implementation reduces smoking (-6.7 pp), sedentary behavior (-4.8 pp), diabetes (-2.7 pp), hypertension (-2.7 pp) and obesity (-2.2 pp), limiting additional hospitalizations to 841. Minimal implementation produces marked deterioration, with hypertension (+21.2 pp), hypercholesterolemia (+12.3 pp) and diabetes (+9.6 pp), alongside +2,610 hospitalizations and EUR472.6 million in non-participation costs.

Conclusions

Atherosclerosis in women is a preventable NCD burden. Policy inaction increases avoidable health and economic costs, while gender-sensitive modelling provides quantitative evidence to guide targeted prevention and more equitable cardiovascular outcomes.

Key messages

• Policy inaction increases cardiovascular risk and costs among women.

• Gender-sensitive modelling improves prevention and equity in cardiovascular health.