Front-of-Package Label Designs: Which One Works Best?

Key Takeaways

• Multi-high-in label outperformed FDA's proposed design
• Study used online randomized controlled trial
• Participants better identified healthy and unhealthy foods
• Label improved recall of nutrition information
• Latin American models provide proven effectiveness

Pulse Analysis

The U.S. Food and Drug Administration has been wrestling with how to present nutrition information on packaged foods, a debate amplified by public figures like RFK Jr who promise a simple traffic‑light system. While the FDA’s draft label focuses on numeric values for saturated fat, sodium, and added sugars, it lacks the intuitive color cues that many health advocates argue are essential for quick consumer decisions. This gap has spurred interest in alternative designs that can convey risk at a glance, especially as policymakers seek tools to combat rising obesity and chronic disease rates.

In a recent online randomized controlled trial, researchers compared several FOP concepts, including the FDA’s draft and a multi‑high‑in label modeled after Chile’s successful warning system. Participants were asked to select the most and least healthful products from a set of images. The multi‑high‑in label, which uses red, yellow, and green signals to denote high, medium, or low levels of key nutrients, dramatically outperformed the FDA version across accuracy, interpretation, and recall metrics. Test takers were more likely to correctly flag products high in sugar, sodium, or saturated fat and less prone to mistakenly view unhealthy items as nutritious.

The implications for U.S. nutrition policy are profound. Adopting a color‑coded, warning‑style label could accelerate the shift toward healthier purchasing patterns, mirroring the measurable public‑health gains seen in Chile, Mexico, and other Latin American markets. Food manufacturers would need to redesign packaging, but the potential reduction in diet‑related illnesses may outweigh compliance costs. As the FDA finalizes its labeling rules, the study’s evidence positions the multi‑high‑in approach as a compelling, data‑driven option for mandatory implementation.