The U.S. faces a growing public health and economic challenge: obesity. More than 40 percent of American adults are obese, costing the health care system an estimated $173 billion annually. And that’s just the tip of the iceberg. Beyond direct medical costs, obesity reduces workforce participation, strains public infrastructure, and slows economic growth.
As Congress works to address this challenge, it needs better tools to account for the far-reaching economic and societal costs of obesity and the efforts to mitigate it. To that end, the Congressional Budget Office should refine how it evaluates the long-term impact of treatment for obesity. As Congress considers proposals to expand Medicare coverage for weight loss drugs, the Congressional Budget Office should adopt scoring methods that account for the full economic and fiscal implications of these therapies.
A new class of therapies — GLP-1 receptor agonists — shows promise to change the trajectory of obesity and its related burdens. Originally developed to treat diabetes, GLP-1s such as semaglutide (Wegovy, Ozempic) and tirzepatide (Mounjaro, Zepbound) are demonstrating significant benefits for weight loss and for reducing such comorbidities as type 2 diabetes and cardiovascular disease.
Clinical results are beginning to reshape medical practice. For example, the American College of Cardiology recently recommended GLP-1s as a first-line treatment for obesity in patients at risk of cardiovascular disease, citing their superior efficacy over lifestyle interventions and favorable safety profile compared to surgery. Clinical trials have shown average weight loss of 15 percent — outcomes previously attainable only through bariatric surgery. This level of efficacy, combined with rising demand, marks a potential inflection point in how obesity is treated.
So far, the Congressional Budget Office has relied on static scoring to evaluate coverage for weight loss drugs. This method estimates the direct budget impact of proposed policies over a 10-year window without accounting for broader economic changes, such as increased workforce participation, reduced disability claims and gains in tax revenue.
The Congressional Budget Office employs static scoring because it is cautious about speculating on uncertain economic feedback effects, focusing instead on the direct budgetary impact of policies. However, this approach fails to capture the long-run and cross-sector spillover effects of health innovations like GLP-1s.
What the Congressional Budget Office misses is that obesity is not solely a medical issue — it’s also a drag on the broader economy. Expanding access to effective treatments could reduce health care spending and enhance productivity and economic growth across sectors.
The food and beverage industry is a great example: early evidence suggests that GLP-1 use may be shifting consumer demand away from ultra-processed foods such as snacks, sweets and baked goods. While disruptive to certain categories of products, these shifts create space for innovation in healthier food products and supply chains.
The labor market, too, stands to benefit from improved obesity outcomes. Obesity-related conditions reduce workforce participation, increase disability claims and diminish productivity. Absenteeism and “presenteeism” — when employees are absent from work or unable to perform at full capacity — are among the most persistent and costly challenges for employers.
In 2023 alone, obesity-related absenteeism cost U.S. employers $82.3 billion, while “presenteeism” added another $160.3 billion in lost productivity. Improving health outcomes at scale could strengthen the labor force and boost tax revenues, yet these macroeconomic effects are not reflected in the Congressional Budget Office’s current scoring models — highlighting the need for tools that better account for the broader economic impact of obesity.
To better evaluate the economic impact of a given therapy, dynamic scoring should be employed. Unlike static models, dynamic scoring accounts for macroeconomic feedback effects — how a policy might influence economic behavior, output and other high-level indicators over time. The Congressional Budget Office has used dynamic scoring in select cases of major legislation.
For example, in evaluating the 2017 Tax Cuts and Jobs Act, which lowered corporate and individual tax rates to spur growth, the Congressional Budget Office and the Joint Committee on Taxation estimated how changes in tax policy would affect GDP, employment and federal revenues. Under current House rules, dynamic scoring is required for bills with a projected fiscal impact of at least 0.25 percent of GDP (approximately $75 billion).
But that economic threshold shouldn’t be the sole determinant for applying such models. Policies like GLP-1 coverage may not meet such thresholds, although their broader impact could be far greater. For example, a bill to expand Medicare coverage for GLP-1s to treat obesity might seem expensive under static scoring. But dynamic scoring could offer a more complete view — capturing future health care savings, productivity gains and cross-sector economic benefits.
Of course, dynamic scoring involves assumptions and uncertainty — but so do all budget forecasts. The greater risk lies in omitting broader economic effects altogether, which could lead to underinvestment in therapies with significant social and economic returns.
Make no mistake, GLP-1s are no silver bullet. Equitable access, clinical oversight and integration with lifestyle support will remain essential. But when used strategically, GLP-1s offer a rare opportunity to address chronic disease in a way that also strengthens economic resilience.
This is not just about reducing body weight — it is about unlocking economic capacity by lowering long-term health care expenditures, strengthening the workforce and relieving pressure on key public systems. The federal budget process should reflect this reality. If the United States is serious about addressing obesity, it must improve how it scores the policies designed to do so.
Sandra Barbosu, Ph.D., is associate director of ITIF’s Center for Life Sciences Innovation, where she researches the economics of science and innovation with a focus on emerging healthcare technologies. She is also an adjunct professor at NYU’s Tandon School of Engineering.
