Research Article
Association Between NOVA Food Processing Classification and Nutri-Score: A Cross-Sectional Analysis of 9,804 Global Food Products
Rahul RKRahul RK1*, Aswathy M2 and Aswathy HV31*, Aswathy M2 and Aswathy HV3
1Department of Acupuncture, Sree Ramakrishna Medical College of Naturopathy and Yogic Sciences, Kulasekharam, Tamil Nadu, India
2Department of Acupuncture, Sree Ramakrishna Medical College of Naturopathy and Yogic Sciences, Kulasekharam, Tamil Nadu, India
3Department of Nutrition and Herbology, Sree Ramakrishna Medical College of Naturopathy and Yogic Sciences, Kulasekharam, Tamil Nadu, India
2Department of Acupuncture, Sree Ramakrishna Medical College of Naturopathy and Yogic Sciences, Kulasekharam, Tamil Nadu, India
3Department of Nutrition and Herbology, Sree Ramakrishna Medical College of Naturopathy and Yogic Sciences, Kulasekharam, Tamil Nadu, India
*Corresponding author:Rahul RK, Department of Acupuncture, Sree Ramakrishna Medical College of Naturopathy and Yogic Sciences, Kulasekharam, Tamil Nadu, India. E-mail Id: terminousmac@gmail.com
Article Information:Submission: 14/05/2026; Accepted: 03/06/2026; Published: 10/06/2026
Copyright: © 2026 Rahul RK, et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
Background: Front-of-pack nutritional labelling systems and food-processing classification frameworks are increasingly used to guide public health nutrition policies and consumer food choices. Nutri-Score evaluates the nutritional profile of foods, while the NOVA classification categorizes foods according
to the extent and purpose of industrial processing. Although both systems are widely applied, the relationship between food processing and nutritional quality remains an important area of investigation.
Objective: To examine the association between NOVA food-processing classification and Nutri-Score grading among 9,804 global food products obtained from the Open Food Facts database, while also exploring discordance between nutrient-profile grading and food-processing classification across major food categories.
Methods: A cross-sectional analytical study was conducted using a dataset of 9,804 food products retrieved from the Open Food Facts database. Products were categorized according to NOVA food-processing groups (1-4) and Nutri-Score grades (A–E). Statistical analysis was performed using SPSS version 27.0. Descriptive statistics, cross-tabulation analysis, Pearson’s chi-square test, and Cramer’s V analysis were used to evaluate associations between food-processing level and nutritional quality.
Results: A statistically significant association was observed between NOVA classification and Nutri-Score grade (χ² = 2012.88, df = 12, p < 0.001). Minimally processed foods (NOVA 1) were predominantly associated with favourable Nutri-Score grades (A and B), whereas ultra-processed foods (NOVA 4) demonstrated a substantially higher proportion of unfavourable grades (D and E). Cramer’s V analysis indicated a moderate-to-strong association between processing intensity and nutritional quality. Important discordance was observed between nutrient-profile grading and food-processing classification, with several ultra-processed foods receiving favourable Nutri-Score ratings.
Conclusion: Higher levels of food processing were strongly associated with poorer Nutri-Score nutritional ratings. However, important discordance was identified between nutrient-profile grading and food-processing classification, suggesting that nutritional quality and industrial processing represent related but distinct dimensions of food evaluation. The findings support growing evidence that ultra-processed foods are more likely to possess unfavourable nutritional characteristics. Integrating nutrient-profile labelling with food-processing classification may improve consumer awareness and strengthen public health nutrition policies.
Objective: To examine the association between NOVA food-processing classification and Nutri-Score grading among 9,804 global food products obtained from the Open Food Facts database, while also exploring discordance between nutrient-profile grading and food-processing classification across major food categories.
Methods: A cross-sectional analytical study was conducted using a dataset of 9,804 food products retrieved from the Open Food Facts database. Products were categorized according to NOVA food-processing groups (1-4) and Nutri-Score grades (A–E). Statistical analysis was performed using SPSS version 27.0. Descriptive statistics, cross-tabulation analysis, Pearson’s chi-square test, and Cramer’s V analysis were used to evaluate associations between food-processing level and nutritional quality.
Results: A statistically significant association was observed between NOVA classification and Nutri-Score grade (χ² = 2012.88, df = 12, p < 0.001). Minimally processed foods (NOVA 1) were predominantly associated with favourable Nutri-Score grades (A and B), whereas ultra-processed foods (NOVA 4) demonstrated a substantially higher proportion of unfavourable grades (D and E). Cramer’s V analysis indicated a moderate-to-strong association between processing intensity and nutritional quality. Important discordance was observed between nutrient-profile grading and food-processing classification, with several ultra-processed foods receiving favourable Nutri-Score ratings.
Conclusion: Higher levels of food processing were strongly associated with poorer Nutri-Score nutritional ratings. However, important discordance was identified between nutrient-profile grading and food-processing classification, suggesting that nutritional quality and industrial processing represent related but distinct dimensions of food evaluation. The findings support growing evidence that ultra-processed foods are more likely to possess unfavourable nutritional characteristics. Integrating nutrient-profile labelling with food-processing classification may improve consumer awareness and strengthen public health nutrition policies.
Keywords:NOVA classification; Nutri-Score; Ultra-processed foods; Food labelling; Nutritional epidemiology; Public health nutrition