Stars versus warnings: Comparison of the Australasian Health Star Rating nutrition labelling system with Chilean Warning Labels

Front-of-Pack Nutrition Labels: Comparing the Nordic Keyhole and Nutri-Score in a Swedish Context

The extent to which different front-of-pack nutrition labels (FOPNLs) agree or contradict each other has been insufficiently investigated. Considering the 2020 proposal from the European Commission to create a harmonized FOPNL, the aim of this study was to assess agreements and disagreements between two FOPNL schemes-the Keyhole and the Nutri-Score-in a Swedish context. The current Keyhole criteria and the updated Nutri-Score 2022 algorithm were applied to 984 food items and their nutrient compositions, obtained from the food database of the Swedish Food Agency. Agreements (Keyhole-eligible and Nutri-Score A or B; or not Keyhole-eligible and Nutri-Score C, D, or E) and disagreements (Keyhole-eligible and Nutri-Score C, D, or E, or not Keyhole-eligible and Nutri-Score A or B) were calculated as percentages for all items and by food group. An agreement was found for 81% of included items. The lowest level of agreement was found for the groups of flour, grains, and rice (62% agreement) and for plant-based meat and fish analogues (33% agreement). There is generally a good level of agreement between the Keyhole and the Nutri-Score for food items on the Swedish market. Large disagreements found for plant-based meat and fish analogues, and products based on cereals/grains, highlight important considerations for the development of a harmonized FOPNL within Europe.

Validation of the Thumbs food classification system as a tool to accurately identify the healthiness of foods

The Thumbs food classification system was developed to assist remote Australian communities to identify food healthiness. This study aimed to assess: (1) the Thumbs system’s alignment to two other food classification systems, the Health Star Rating (HSR) and the Northern Territory School Canteens Guidelines (NTSCG); (2) its accuracy in classifying ‘unhealthy’ (contributing to discretionary energy and added sugars) and ‘healthy’ products against HSR and NTSCG; (3) areas for optimisation. Food and beverage products sold between 05/2018 and 05/2019 in fifty-one remote stores were classified in each system. System alignment was assessed by cross-tabulating percentages of products, discretionary energy and added sugars sold assigned to the same healthiness levels across the systems. The system/s capturing the highest percentage of discretionary energy and added sugars sold in ‘unhealthy’ products and the lowest levels in ‘healthy’ products were considered the best performing. Cohen’s κ was used to assess agreement between the Thumbs system and the NTSCG for classifying products as healthy. The Thumbs system classified product healthiness in line with the HSR and NTSCG, with Cohen’s κ showing moderate agreement between the Thumbs system and the NTSCG (κ = 0·60). The Thumbs system captured the most discretionary energy sold (92·2 %) and added sugar sold (90·6 %) in unhealthy products and the least discretionary energy sold (0 %) in healthy products. Modifications to optimise the Thumbs system include aligning several food categories to the NTSCG criteria and addressing core/discretionary classification discrepancies of fruit juice/drinks. The Thumbs system offers a classification algorithm that could strengthen the HSR system.

Nutrition Classification Schemes for Informing Nutrition Policy in Australia: Nutrient-Based, Food-Based, or Dietary-Based?

Background

Policy makers are increasingly using nutrition classification schemes (NCSs) to assess a food's health potential for informing nutrition policy actions. However, there is wide variability among the NCSs implemented and no standard benchmark against which their contrasting assessments can be validated.

Objectives

This study aimed to compare the agreement of nutrient-, food-, and dietary-based NCSs in their assessment of a food's health potential within the Australian food supply, and examine the conceptual underpinnings and technical characteristics that explain differences in performance.

Methods

A dataset combining food compositional data from the Mintel Global New Products Database and the Australian Food Composition Database (AUSNUT 2011-2012) (n = 7322) was assembled. Products were classified by 7 prominent NCSs that were selected as representative of one or other of 1) nutrient-based NCSs [the Chilean nutrient profile model (NPM), Health Star Rating (HSR), Nutri-Score, the WHO European Region's NPM (WHO-Euro NPM), and the Pan American Health Organization's (PAHO) NPM]; 2) food-based NCS (NOVA), and 3) dietary-based NCS [Australian Dietary Guidelines (ADGs)].

Results

The PAHO NPM classified the lowest proportion (22%) of products as "healthy", and the HSR the highest (63%). The PAHO NPM, NOVA, WHO-Euro NPM, and the Chilean NPM classified >50% of products as "unhealthy," and the ADGs, HSR, and Nutri-Score classified <50% of products as "unhealthy." The HSR and Nutri-Score had the highest pairwise agreement (κ = 0.7809, 89.70%), and the PAHO NPM and HSR the lowest (κ = 0.1793, 53.22%). Characteristics of NCSs that more effectively identified ultraprocessed and discretionary foods were: category-specific assessment, the classification of categories as always "healthy" or "unhealthy," consideration of level of food processing, thresholds for "risk" nutrients that do not penalize whole foods; and no allowance for the substitution of ingredients.

Conclusions

Wide variation was observed in agreement of the assessment of a food's health potential among the NCSs analyzed due to differing conceptual underpinnings and technical characteristics.

Healthy or Not Healthy? A Mixed-Methods Approach to Evaluate Front-of-Pack Nutrition Labels as a Tool to Guide Consumers

This study explored how South African food labels could be improved, to enhance customer evaluation of the overall healthiness of packaged food. Focus was given to the comparison of front-of-pack (FOP) nutrition labels as a quick assessment tool. The exploratory sequential mixed-methods design used qualitative interviews (n = 49) to gain insight into labeling challenges and select FOP nutrition labels for consumer testing. Consumers (n = 1261) randomly assessed two out of six possible FOP nutrition labels relative to a ‘no-label’ control in one of 12 online surveys, applied to a fictitious cereal product. A mixed-model analysis of variance was used to compare the differences in health ratings for the different FOP nutrition labels. The interviews revealed three themes for label improvement, that are presented over three time horizons. In terms of helping consumers identify less healthy products, the effect sizes were most prominent for health warnings (p < 0.01) and low health star ratings (p < 0.01). The findings of this research not only clarify whether FOP nutrition labeling formats used in other regions such as Europe, South America and Australia could be useful in the South African context, but they can assist policymakers and decision-makers in selecting an effective FOP label.

Polish Consumers' Understanding of Different Front-of-Package Food Labels: A Randomized Experiment

Dietary practices are a key behavioral factor in chronic disease prevention; one strategy for improving such practices population-wise involves front-of-package labels (FoPL). This online randomized study, conducted in a quota-based sample of 1159 Polish adults (mean age = 40.9 ± 15.4 years), assessed the objective understanding of five FoPL: Health Star Rating, Multiple Traffic Lights, NutriScore, Reference Intakes (RI) and Warning Label. Objective understanding was evaluated by comparing results of two nutritional quality ranking tasks (without/with FoPL) using three food categories (breakfast cereals, cakes, pizza). Associations between FoPL exposure and objective understanding were assessed via multivariable ordinal logistic regression. Compared to RI and across food categories, significant improvement in objective understanding was seen for NutriScore (OR = 2.02; 95% CI: 1.41–2.91) and Warning Label (OR = 1.61; 95% CI: 1.12–2.32). In age-stratified analyses, significant improvement in objective understanding compared to RI emerged mainly among adults aged 18–30 years randomized to NutriScore (all food categories: OR = 3.88; 95% CI: 2.04–7.36; cakes: OR = 6.88; 95% CI: 3.05–15.51). Relative to RI, NutriScore was associated with some improvement in objective understanding of FoPL across and within food categories, especially among young adults. These findings contribute to the ongoing debate about an EU-wide FoPL model.

An Experimental Comparison of the Impact of 'Warning' and 'Health Star Rating' FoP Labels on Adolescents' Choice of Breakfast Cereals in New Zealand

This research investigated the performance of the red, octagonal Vienna Convention traffic ‘STOP’ sign as a front of pack (FoP) warning nutritional label. While the Vienna Convention traffic light system is an established FoP label, the potential of the ‘STOP’ sign in the role has not been investigated. The performance of the ‘STOP’ label was compared with that of a single star (low nutritional value) Australasian Health Star Rating (HSR) label using a fractionally replicated Latin square design. The labels were presented on choice diads of cold breakfast cereal packets. The sample of 240 adolescents aged 16–18 was drawn from a secondary school in the South Island of New Zealand. A large and significant main effect was observed at the p < 0.01 level for the difference between the ’STOP’ sign and the control condition (no nutritional FoP label), and at p < 0.05 for the difference between the HSR and the ‘STOP’ label. There was no significant difference between the HSR FoP and the control condition. A significant non-additivity (interaction) (p < 0.01) was also observed via the fractional replication. The results indicate that the Vienna Convention ‘STOP’ sign is worthy of further research with regard to its potential as an FoP nutritional label.

Evaluating Nutrient-Based Indices against Food- and Diet-Based Indices to Assess the Health Potential of Foods: How Does the Australian Health Star Rating System Perform after Five Years?

Nutrient-based indices are commonly used to assess the health potential of individual foods for nutrition policy actions. This study aimed to evaluate the nutrient profile-informed Australian Health Star Rating (HSR), against NOVA and an index informed by the Australian Dietary Guidelines (ADGs), to determine the extent of alignment. All products displaying an HSR label in the Australian marketplace between June 2014 and June 2019 were extracted from the Mintel Global New Product Database, and classified into one of four NOVA categories, and either as an ADG five food group (FFG) food or discretionary food. Of 4451 products analysed, 76.5% were ultra-processed (UP) and 43% were discretionary. The median HSR of non-UP foods (4) was significantly higher than UP foods (3.5) (p < 0.01), and the median HSR of FFG foods (4) was significantly higher than discretionary foods (2.5) (p < 0.01). However, 73% of UP foods, and 52.8% of discretionary foods displayed an HSR ≥ 2.5. Results indicate the currently implemented HSR system is inadvertently providing a ‘health halo’ for almost ¾ of UP foods and ½ of discretionary foods displaying an HSR. Future research should investigate whether the HSR scheme can be reformed to avoid misalignment with food-and diet-based indices.