The impact of restaurant menu eco labels on consumer meal selections: a randomized controlled trial.
レストランメニューのエコラベルが消費者の食事選択に与える影響：ランダム化比較試験 (AI 翻訳)
Alexandria E. Reimold, Jennifer Falbe, Brent Kim, A. Musicus, Nina Carr, Raychel Santo, Clara Cho, Cindy W. Leung, Christina A. Roberto, Julia A. Wolfson
🤖 gxceed AI 要約
日本語
本ランダム化比較試験では、5種類の気候ラベル（数値表示、グレード、信号機、警告、対照）が消費者の食事選択に与える影響を評価しました。その結果、信号機ラベルと警告ラベルが、栄養価を向上させつつ温室効果ガス排出量を有意に削減することが示されました。
English
This online RCT with 6,221 US adults tested five climate label designs on fast-food menus. Traffic Light and Warning labels significantly improved meal nutritional quality and reduced greenhouse gas emissions compared to a control label.
Unofficial AI-generated summary based on the public title and abstract. Not an official translation.
📝 gxceed 編集解説 — Why this matters
日本のGX文脈において
日本の外食産業でも、食品選択における環境表示の有効性が注目されています。本知見は、日本版「健康・環境ラベル」の設計や消費者行動変容施策に示唆を与える可能性があります。
In the global GX context
This study provides robust experimental evidence that interpretive climate labels (Traffic Light, Warning) can shift consumer behavior toward lower-carbon, healthier meals. It supports the global push for mandatory eco-labels on food, aligning with EU and UK discussions on front-of-pack climate labeling.
👥 読者別の含意
🔬研究者:Evidence that interpretive labels outperform numeric labels in shifting behavior, with implications for choice architecture and climate communication.
🏢実務担当者:Restaurant chains can adopt Traffic Light or Warning labels to nudge customers toward sustainable menu items without restricting choice.
🏛政策担当者:Supports the effectiveness of mandatory interpretive eco-labels as a low-cost policy tool to reduce food-related emissions.
📄 Abstract（原文）
INTRODUCTION Food systems account for ∼30% of the greenhouse gas emissions (GHGE) that contribute to climate change. Climate labels on restaurant menus may help consumers decrease their food-related climate impact and improve meal nutrition given that environmentally sustainable diets are also healthier. This study evaluated the degree to which different climate labels promoted healthier and lower climate impact food choices. STUDY DESIGN Online RCT conducted in 2024, analyzed in 2025. SETTING/PARTICIPANTS A national sample of 6,221 adults benchmarked to the US Census on sex, race, ethnicity, and age. INTERVENTION Participants were randomized to view a fast-food menu with either a control label or one of four climate label designs: (1) Numeric; (2) Climate Grade; (3) Traffic Light; or (4) Warning. Labels appeared alongside main menu items and were based on total supply chain GHGE associated with each item. Participants were instructed to select a hypothetical lunch meal order. MAIN OUTCOME MEASURES The main outcomes of this study were the selected meals' nutritional quality (measured using a modified Nutrient Profile Index [NPI] score) and GHGE in kgCO2e per meal. RESULTS Compared with participants in the control condition (mean NPI score=50.6, SE(0.28)), those in the Traffic Light (mean NPI score=51.3, SE(0.28); p=0.013) and Warning (mean NPI score=51.3, SE(0.28); p=0.015) label groups chose significantly healthier meals (i.e., higher NPI score). Compared to the control (mean GHGE=27.5, SE(0.97)), all climate labels resulted in meals with significantly lower GHGE. Participants in the Traffic Light condition selected meals with the lowest GHGE (mean GHGE=22.6, SE(0.97); p<0.001), followed by Warning (mean GHGE=23.9, SE(0.97); p<0.001), Grade (mean GHGE=24.6, SE(0.97); p=0.004), and Numeric (mean GHGE=24.7, SE(0.98); p=0.005). CONCLUSIONS Interpretive climate labels, particularly Traffic Light and Warning label designs, are a promising way of improving the nutritional quality while reducing the climate impact of restaurant meal orders. TRIAL REGISTRATION (https://clinicaltrials.gov/study/NCT06909019).
🔗 Provenance — このレコードを発見したソース
- semanticscholar https://doi.org/10.1016/j.amepre.2026.108265first seen 2026-05-05 22:18:21
gxceed は公開メタデータに基づく研究支援データセットです。要約・翻訳・解説は AI 支援で生成されています。 最終的な解釈・検証は利用者が原典資料に基づいて行うことを前提とします。