Context and purpose
- The statement provides projections of cardiovascular disease (CVD) and stroke burden in women through 2050, aiming to inform clinical and public health planning across the life course.
Study design and data sources
- Projections derive from historical trends observed in multiple national datasets, including NHANES (2015–2020), the Medical Expenditure Panel Survey (MEPS; 2015–2019), and census population estimates.
- The analysis estimates prevalence trends for cardiovascular risk factors defined by suboptimal levels of Life’s Essential 8, as well as for clinical CVD and stroke, with stratification by age and race/ethnicity.
Key prevalence projections in adult women
- Hypertension: increase from 48.6% in 2020 to 59.1% by 2050.
- Diabetes: rise from 14.9% to 25.3%.
- Obesity: up from 43.9% to 61.2%.
- Hypercholesterolemia: expected decline from 42.1% to 22.3%.
- Suboptimal lifestyle factors: diet quality, insufficient physical activity, and smoking are projected to decline; sleep insufficiency is projected to increase.
- Clinically defined CVD and stroke: coronary disease from 6.85% to 8.21%; heart failure from 2.45% to 3.60%; stroke from 4.14% to 6.74%; atrial fibrillation from 1.58% to 2.31%; total CVD and stroke burden from 10.7% to 14.4%.
Key projections in younger females (ages 2–19)
- Obesity is projected to rise from 19.6% to 32.0%.
Subgroup patterns and uncertainties
- Adverse trends are anticipated to be more pronounced among women and girls identifying as American Indian/Alaska Native, multiracial, Black, or Hispanic.
- The analysis acknowledges reliance on historical data and modeling assumptions, with inherent uncertainty in long-term projections.
Operational implications
- The authors emphasize a need for sustained, life-course–oriented clinical and public health interventions to address evolving risk factor profiles and disease burden in women.
Limitations
- The summary notes uncertainty and limitations related to projection methods and population heterogeneity, without introducing new data beyond the cited sources.