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Background Socioeconomic status has an important effect on cardiovascular disease (CVD). Data on the economic implications of CVD by socioeconomic status are needed to inform healthcare planning. Objectives The aim of this study was to project new-onset CVD and related health economic outcomes in Australia by socioeconomic status from 2021 to 2030. Methods A dynamic population model was built to project annual new-onset CVD by socioeconomic quintile in Australians aged 40–79 years from 2021 to 2030. Cardiovascular risk was estimated using the Pooled Cohort Equation (PCE) from Australian-specific data, stratified for each socioeconomic quintile. The model projected years of life lived, quality- adjusted life-years (QALYs), acute healthcare medical costs, and productivity losses due to new-onset CVD. All outcomes were discounted by 5% annually. Results PCE estimates showed that 8.4% of people in the most disadvantaged quintile were at high risk of CVD, compared with 3.7% in the least disadvantaged quintile ( p < 0.001). From 2021 to 2030, the model projected 32% more cardiovascular events in the most disadvantaged quintile compared with the least disadvantaged (127,070 in SE 1 vs. 96,222 in SE 5). Acute healthcare costs in the most disadvantaged quintile were Australian dollars (AU$) 183 million higher than the least disadvantaged, and the difference in productivity costs was AU$959 million. Removing the equity gap (by applying the cardiovascular risk from the least disadvantaged quintile to the whole population) would prevent 114,822 cardiovascular events and save AU$704 million of healthcare costs and AU$3844 million of lost earnings over the next 10 years. Conclusion Our results highlight the pressing need to implement primary prevention interventions to reduce cardiovascular health inequity. This model provides a platform to incorporate socioeconomic status into health economic models by estimating which interventions are likely to yield more benefits in each socioeconomic quintile. Supplementary Information The online version contains supplementary material available at 10.1007/s40273-021-01127-1.

Aims/hypothesis The aim of this study was to determine the long-term cost-effectiveness and return on investment of implementing a structured lifestyle intervention to reduce excessive gestational weight gain and associated incidence of gestational diabetes mellitus (GDM) and type 2 diabetes mellitus. Methods A decision-analytic Markov model was used to compare the health and cost-effectiveness outcomes for (1) a structured lifestyle intervention during pregnancy to prevent GDM and subsequent type 2 diabetes; and (2) current usual antenatal care. Life table modelling was used to capture type 2 diabetes morbidity, mortality and quality-adjusted life years over a lifetime horizon for all women giving birth in Australia. Costs incorporated both healthcare and societal perspectives. The intervention effect was derived from published meta-analyses. Deterministic and probabilistic sensitivity analyses were used to capture the impact of uncertainty in the model. Results The model projected a 10% reduction in the number of women subsequently diagnosed with type 2 diabetes through implementation of the lifestyle intervention compared with current usual care. The total net incremental cost of intervention was approximately AU$70 million, and the cost savings from the reduction in costs of antenatal care for GDM, birth complications and type 2 diabetes management were approximately AU$85 million. The intervention was dominant (cost-saving) compared with usual care from a healthcare perspective, and returned AU$1.22 (95% CI 0.53, 2.13) per dollar invested. The results were robust to sensitivity analysis, and remained cost-saving or highly cost-effective in each of the scenarios explored. Conclusions/interpretation This study demonstrates significant cost savings from implementation of a structured lifestyle intervention during pregnancy, due to a reduction in adverse health outcomes for women during both the perinatal period and over their lifetime. Graphical abstract