Estimated health and economic impacts of Nutri-Score labelling in England: a modelling study
Abstract
Background: Out-of-home (OOH) food intake is a key contributor to obesity and cardiovascular disease (CVD) risk. Evidence shows that interpretive nutrition labels, such as the Nutri-Score (NS) on OOH menus, can shift consumers towards healthier choices. To inform policy decisions, we modelled the health and economic impact of NS labelling in England’s OOH food sector.
Methods: We used IMPACTNCD, a validated discrete-time stochastic dynamic microsimulation. We created a synthetic population of England aged 30-99 years using data from the Office for National Statistics population projections, the Health Survey for England, the National Diet and Nutrition Survey, and Clinical Practice Research Datalink Aurum, linked to Hospital Episode Statistics and ONS mortality records. We simulated two scenarios over 20 years (2024-2043): (1) NS in large OOH businesses (≥250 employees) and (2) in all OOH businesses, both compared to a no-label scenario. The modelled effect on energy intake was informed by a meta-analysis of two field studies, and we assumed a dietary compensation of 26.5% based on two systematic reviews.
Results: Preliminary results estimate that NS in large OOH businesses could prevent or postpone 64,000 (95% uncertainty interval: 23,000-110,000) obesity cases and 1,600 (310-3,900) all-cause deaths, gain 63,000 (29,000-98,000) quality-adjusted life years (QALYs) and save £3.8bn (£1.7bn-£5.8bn) in societal costs (healthcare, informal, social care, productivity) over 20 years. Labels in all OOH businesses could prevent or postpone 310,000 (150,000-460,000) obesity cases and 9,000 (3,500-19,000) all-cause deaths, gain 350,000 (160,000-530,000) QALYs and save £21bn (£9.5bn-£31bn) in societal costs.
Conclusions: This is the first modelled evidence on the health and economic impacts of implementing NS labels in the OOH food sector. NS is projected to reduce obesity and CVD mortality. Benefits would be greater if implementation were scaled to all OOH businesses.
Key messages: • Nutri-Score labelling in large OOH food businesses is projected to have a beneficial impact in England.
• Nutri-Score labelling in all OOH food businesses will likely maximise impact.
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BibTeX
@article{alves2026estimated,
title = {{Estimated health and economic impacts of Nutri-Score labelling in England: a modelling study}},
author = {F Alves and M O’Flaherty and A Finlay and Z Toumpakari and N Townsend and A Jones and J Garbutt and C Kypridemos and E Robinson and Z Colombet},
journal = {The European Journal of Public Health},
year = {2026},
month = oct,
doi = {10.1093/eurpub/ckag169.496},
url = {https://doi.org/10.1093/eurpub/ckag169.496},
note = {CC BY-NC 4.0},
}
RIS
TY - JOUR
TI - Estimated health and economic impacts of Nutri-Score labelling in England: a modelling study
AU - F Alves
AU - M O’Flaherty
AU - A Finlay
AU - Z Toumpakari
AU - N Townsend
AU - A Jones
AU - J Garbutt
AU - C Kypridemos
AU - E Robinson
AU - Z Colombet
PY - 2026
DA - 2026/10/01
JO - The European Journal of Public Health
DO - 10.1093/eurpub/ckag169.496
UR - https://doi.org/10.1093/eurpub/ckag169.496
AB - Background: Out-of-home (OOH) food intake is a key contributor to obesity and cardiovascular disease (CVD) risk. Evidence shows that interpretive nutrition labels, such as the Nutri-Score (NS) on OOH menus, can shift consumers towards healthier choices. To inform policy decisions, we modelled the health and economic impact of NS labelling in England’s OOH food sector. Methods: We used IMPACTNCD, a validated discrete-time stochastic dynamic microsimulation. We created a synthetic population of England aged 30-99 years using data from the Office for National Statistics population projections, the Health Survey for England, the National Diet and Nutrition Survey, and Clinical Practice Research Datalink Aurum, linked to Hospital Episode Statistics and ONS mortality records. We simulated two scenarios over 20 years (2024-2043): (1) NS in large OOH businesses (≥250 employees) and (2) in all OOH businesses, both compared to a no-label scenario. The modelled effect on energy intake was informed by a meta-analysis of two field studies, and we assumed a dietary compensation of 26.5% based on two systematic reviews. Results: Preliminary results estimate that NS in large OOH businesses could prevent or postpone 64,000 (95% uncertainty interval: 23,000-110,000) obesity cases and 1,600 (310-3,900) all-cause deaths, gain 63,000 (29,000-98,000) quality-adjusted life years (QALYs) and save £3.8bn (£1.7bn-£5.8bn) in societal costs (healthcare, informal, social care, productivity) over 20 years. Labels in all OOH businesses could prevent or postpone 310,000 (150,000-460,000) obesity cases and 9,000 (3,500-19,000) all-cause deaths, gain 350,000 (160,000-530,000) QALYs and save £21bn (£9.5bn-£31bn) in societal costs. Conclusions: This is the first modelled evidence on the health and economic impacts of implementing NS labels in the OOH food sector. NS is projected to reduce obesity and CVD mortality. Benefits would be greater if implementation were scaled to all OOH businesses. Key messages: • Nutri-Score labelling in large OOH food businesses is projected to have a beneficial impact in England. • Nutri-Score labelling in all OOH food businesses will likely maximise impact.
SN - 1101-1262
SN - 1464-360X
ER -