The Burden and Impact of Intervention Strategies for Heart Failure in China (2025–2035): A Health-Augmented Macroeconomic Modeling Study
Abstract
Background
Heart failure (HF) imposes a growing public health and macroeconomic burden in low- and middle-income countries (LMICs), yet its long-term economic implications remain unquantified. China, characterized by rapid population aging and escalating cardiovascular risks, provides a critical setting to model HF’s economic impact.
Methods
Using data from the Global Burden of Disease Study 2021, China Cardiovascular Association Registry, and national insurance databases, we quantified the macroeconomic burden of heart failure (2025–2035) through a health-augmented macroeconomic model. We evaluated three interventions: BNP screening (adults ≥40 years), intensive blood pressure control (hypertensive patients), and guideline-directed medical therapy (GDMT) for HF with reduced ejection fraction (HFrEF). Costs are reported in 2017 international dollars (INT$).
Findings
By 2035, HF cases in China are projected to reach 22·7 million (95% UI: 9·5–36·9 million), with an age-standardized prevalence of 760·65 per 100,000 (283·21–1,340·77). The cumulative economic burden (2025–2035) is estimated at INT$1,001·1 billion (733·4–1,346·6 billion), representing 0·256%(0·188%–0·344%) of annual GDP, driven by labor force attrition (72·1%; 64·4–74·8%) and direct medical costs (27·9%; 25·2–35·6%). Three interventions could reduce the total burden by 12·5%: BNP screening (25% coverage among adults≥40 years) could save INT$78·5 billion (62·8–94·1 billion; 8·10% burden reduction; cost-benefit ratio= 0·49; 0·39–0·59); intensive blood pressure control (41·4% coverage among hypertensive patients) could reduce costs by INT$27·5 billion (25·1–29·9 billion; 2·74% reduction; ratio=0·22; 0·20–0·24); and GDMT for incident HFrEF patients could yield savings of INT$17·0 billion (12·8–22·4 billion; 1·70% reduction; ratio=0·48; 0·36–0·63).
Interpretation
This study highlights HF’s dual clinical and macroeconomic burden in China, advocating three scalable strategies: nationwide BNP screening in primary care, subsidized hypertension management, and GDMT optimization. These interventions might offer a blueprint for LMICs to mitigate HF-related economic losses amid demographic aging.
Funding
This study was supported by grants from the Noncommunicable Chronic Diseases-National Science and Technology Major Project (No: 2023ZD0504600); Capital’s Funds for Health Improvement and Research (2022-1-4052); the National High-Level Hospital Clinical Research Funding (BJYY-2023-070); the National Natural Science Foundation of China (No. 82170396); and the CAMS Innovation Fund for Medical Sciences (2021-I2M-1-050).
Research in Context
Evidence Before This Study
We systematically searched MEDLINE, PubMed, and Google Scholar for studies published between 1990–2025 using terms including “heart failure,” “economic burden,” “economic cost.” Existing literature predominantly focused on cost-of-illness analyses in high-income countries, aggregating direct medical and indirect productivity costs. While the Global Burden of Disease Study provided epidemiological estimates, no prior study quantified the macroeconomic impact of heart failure (HF) in rapidly aging populations like China. Evidence on cost-effective interventions tailored to China’s healthcare systems, such as biomarker screening or workforce-targeted therapies, remained sparse.
Added Value of This Study
This study presents the first macroeconomic projections of HF in China, forecasting that by 2035, the number of HF cases will reach 22·7 million (uncertainty interval [UI]: 9·5 – 36·9 million), with an age-standardized prevalence rate of 760·65 (UI: 283·2–1,340·8) per 100,000 people. Age-specific analyses reveal a steep rise in HF prevalence across all age groups in China, with the most marked increases among older adults: the 60–64 years cohort is projected to rise from 0·974% (711,347 cases) in 2021 to 1·269% (1·39 million cases) by 2035 (30·3% prevalence increase; 95·5% case surge), while younger populations (35 – 39 years) show a 14·9% relative rise, underscoring the urgent need for life-course prevention strategies to address accelerating burdens in aging and younger demographics.The total economic burden from 2025 to 2035 is projected at INT$1,001·1 billion (UI: 733·4–1,345·6 billion, at constant 2017 prices), which accounts for 0·256% (UI: 0·188%–0·344%) of China’s GDP annually. This burden is driven predominantly by indirect costs (72·1%), mainly resulting from reduced labor force participation and productivity losses, with direct medical costs contributing 27·9%.Three cost-effective interventions—BNP screening (25% coverage among adults ≥40 years; 8·10% burden reduction), intensive blood pressure control (41·4% coverage in hypertensive patients; 2·74% reduction), and guideline-directed medical therapy (GDMT) for HFrEF patients (1·70% reduction)—could collectively reduce the total economic burden by 12·5%, saving up to INT$123·0 billion (UI: 100·65 – 146·39billion) over a decade, with favorable cost-benefit ratios (0·221 – 0·489) underscoring scalability in resource-limited settings.
Implications of All the Available Evidence
The escalating burden of HF in China reflects challenges faced by low- and middle-income countries (LMICs) navigating demographic aging and epidemiological shifts, underscoring the imperative to integrate HF prevention into national health agendas. Our findings align with China’s Healthy China 2030 initiative, the United Nations Sustainable Development Goals and Global health 2050, advocating for policies that prioritize prevention, early detection (e.g., BNP screening), and optimized chronic disease management (e.g., GDMT) to enhance workforce sustainability. Cost-effective interventions such as BNP screening and GDMT optimization are scalable across LMICs with limited resources, offering pathways to mitigate long-term societal and economic impacts. The COVID-19 pandemic has further exposed vulnerabilities in low-income and rural healthcare systems, necessitating targeted investments in digital health technologies and infrastructure to address care disparities. Policymakers must prioritize data-driven strategies combating rural-urban gaps in access, strengthening primary care capacity, and leveraging innovation to ensure equitable and sustainable HF management in aging populations globally.
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