Dataset Information

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?

ABSTRACT: 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.

SUBMITTER: Dickie S

PROVIDER: S-EPMC7284529 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

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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?

Dickie Sarah S Woods Julie L JL Baker Phillip P Elizabeth Leonie L Lawrence Mark A MA

Nutrients 20200518 5

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 c ...[more]

PMID: 32443570

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Project description:Front-of-package nutrition labelling (FOPNL) is known as an effective tool that can encourage healthier food choices and food reformulation. A very interesting type of FOPNL is grading schemes. Our objective was to compare two market-implemented grading schemes-European Nutri-Score (NS) and Australian Health Star Rating (HSR), using large Slovenian branded foods database. NS and HSR were used for profiling 17,226 pre-packed foods and drinks, available in Slovenian food supply dataset (2020). Alignment between models was evaluated with agreement (% of agreement and Cohen's Kappa) and correlation (Spearman rho). The 12-month nationwide sales-data were used for sale-weighing, to address market-share differences. Study results indicated that both models have good discriminatory ability between products based on their nutritional composition. NS and HSR ranked 22% and 33% of Slovenian food supply as healthy, respectively. Agreement between NS and HSR was strong (70%, κ = 0.62) with a very strong correlation (rho = 0.87). Observed profiling models were most aligned within food categories Beverages and Bread and bakery products, while less aligned for Dairy and imitates and Edible oils and emulsions. Notable disagreements were particularly observed in subcategories of Cheese and processed cheeses (8%, κ = 0.01, rho = 0.38) and Cooking oils (27%, κ = 0.11, rho = 0.40). Further analysis showed that the main differences in Cooking oils were due to olive oil and walnut oil, which are favoured by NS and grapeseed, flaxseed and sunflower oil that are favoured by HSR. For Cheeses and cheese products, we observed that HSR graded products across the whole scale, with majority (63%) being classified as healthy (≥3.5 *), while NS mostly graded lower scores. Sale-weighting analyses showed that offer in the food supply does not always reflect the sales. Sale-weighting increased overall agreement between profiles from 70% to 81%, with notable differences between food categories. In conclusion, NS and HSR were shown as highly compliant FOPNLs with few divergences in some subcategories. Even these models do not always grade products equally high, very similar ranking trends were observed. However, the observed differences highlight the challenges of FOPNL ranking schemes, which are tailored to address somewhat different public health priorities in different countries. International harmonization can support further development of grading type nutrient profiling models for the use in FOPNL, and make those acceptable for more stake-holders, which will be crucial for their successful regulatory implementation.

Project description:In Australia, manufacturers can use two government-endorsed approaches to advertise product healthiness: the Health Star Rating (HSR) front-of-pack nutrition labelling system, and health claims. Related, but different, algorithms determine the star rating of a product (the HSR algorithm) and eligibility to display claims (the Nutrient Profiling Scoring Criterion (NPSC) algorithm). The objective of this study was to examine the agreement between the HSR and NPSC algorithms. Food composition information for 41,297 packaged products was extracted from The George Institute's FoodSwitch database. HSR and the NPSC scores were calculated, and the proportion of products in each HSR category that were eligible to display a health claim under the NPSC was examined. The highest agreement between the HSR scoring algorithm and the NPSC threshold to determine eligibility to display a health claim was at the HSR cut-off of 3.5 stars (k = 0.83). Overall, 97.3% (n = 40,167) of products with star ratings of 3.5 or higher were also eligible to display a health claim, and 94.3% (n = 38,939) of products with star ratings less than 3.5 were ineligible to display a health claim. The food group with greatest divergence was "edible oils", with 45% products (n = 342) with HSR >3.5, but 64% (n = 495) eligible to display a claim. Categories with large absolute numbers of products with HSR <3.5, but eligible to display a claim, were "yoghurts and yoghurt drinks" (335 products, 25.4%) and "soft drinks" (299 products, 29.7%). Categories with a large number of products with HSR ≥3.5, but ineligible to display a claim, were "milk" (260 products, 21.2%) and "nuts and seeds" (173 products, 19.7%). We conclude that there is good agreement between the HSR and the NPSC systems overall, but divergence in some food groups is likely to result in confusion for consumers, particularly where foods with low HSRs are eligible to display a health claim. The alignment of the NPSC and HSR scoring algorithms should be improved.

Project description:BackgroundThe Health Star Rating (HSR) is the government-endorsed front-of-pack labeling system in Australia and New Zealand.ObjectivesWe aimed to examine prospective associations of a dietary index (DI) based on the HSR, as an indicator of overall diet quality, with all-cause and cardiovascular disease (CVD) mortality.MethodsWe utilized data from the national population-based Australian Diabetes, Obesity and Lifestyle Study. The HSR-DI at baseline (1999-2000) was constructed by 1) calculation of the HSR points for individual foods in the baseline FFQ, and 2) calculation of the HSR-DI for each participant based on pooled HSR points across foods, weighted by the proportion of energy contributed by each food. Vital status was ascertained by linkage to the Australian National Death Index. Associations of HSR-DI with mortality risk were assessed by Cox proportional hazards regression.ResultsAmong 10,025 eligible participants [baseline age: 51.6 ± 14.3 y (mean ± standard deviation)] at entry, higher HSR-DI (healthier) was associated with higher consumption of healthy foods such as fruits, vegetables, and nuts, and lower consumption of discretionary foods such as processed meats and confectionery (P-trend < 0.001 for each). During a median follow-up of 16.9 y, 1682 deaths occurred with 507 CVD deaths. In multivariable models adjusted for demographic characteristics, lifestyle factors, and medical conditions, higher HSR-DI was associated with lower risk of all-cause mortality, with a hazard ratio (95% confidence interval) of 0.80 (0.69, 0.94; P-trend < 0.001) comparing the fifth with the first HSR-DI quintile. A corresponding inverse association was observed for CVD mortality (0.71; 0.54, 0.94; P-trend = 0.008).ConclusionsBetter diet quality as defined by the HSR-DI was associated with lower risk of all-cause and CVD mortality among Australian adults. Our findings support the use of the HSR nutrient profiling algorithm as a valid tool for guiding consumer food choices.

Project description:BackgroundStar Rating Assessment (SRA) was initiated in 2015 in Tanzania aiming at improving the quality of services provided in Primary Healthcare (PHC) facilities. Social accountability (SA) is among the 12 assessment areas of SRA tools. We aimed to assess the SA performance and its predictors among PHC facilities in Tanzania based on findings of a nationwide reassessment conducted in 2017/18.MethodsWe used the SRA database with results of 2017/2018 to perform a cross-sectional secondary data analysis on SA dataset. We used proportions to determine the performance of the following five SA indicators: functional committees/boards, display of information on available resources, addressing local concerns, health workers' engagement with local community, and involvement of community in facility planning process. A facility needed four indicators to be qualified as socially accountable. Adjusted odds ratios (AOR) with 95% confidence intervals (CI) were used to determine facilities characteristics associated with SA, namely location (urban or rural), ownership (private or public) and level of service (hospital, health centre or dispensary).ResultsWe included a total of 3,032 PHC facilities of which majority were dispensaries (86.4%), public-owned (76.3%), and located in rural areas (76.0%). On average, 30.4% of the facilities were socially accountable; 72.0% engaged with local communities; and 65.5% involved communities in facility planning process. Nevertheless, as few as 22.5% had functional Health Committees/Boards. A facility was likely to be socially-accountable if public-owned [AOR 5.92; CI: 4.48-7.82, p = 0.001], based in urban areas [AOR 1.25; 95% CI: 1.01-1.53, p = 0.038] or operates at a level higher than Dispensaries (Health centre or Hospital levels).ConclusionMost of the Tanzanian PHC facilities are not socially accountable and therefore much effort in improving the situation should be done. The efforts should target the lower-level facilities, private-owned and rural-based PHC facilities. Regional authorities must capacitate facility committees/boards and ensure guidelines on SA are followed.

Project description:The Health Star Rating (HSR) is an interpretive front-of-pack labelling system that rates the overall nutritional profile of packaged foods. The algorithm underpinning the HSR includes total sugar content as one of the components. This has been criticised because intrinsic sugars naturally present in dairy, fruits, and vegetables are treated the same as sugars added during food processing. We assessed whether the HSR could better discriminate between core and discretionary foods by including added sugar in the underlying algorithm.Nutrition information was extracted for 34,135 packaged foods available in The George Institute's Australian FoodSwitch database. Added sugar levels were imputed from food composition databases. Products were classified as 'core' or 'discretionary' based on the Australian Dietary Guidelines. The ability of each of the nutrients included in the HSR algorithm, as well as added sugar, to discriminate between core and discretionary foods was estimated using the area under the curve (AUC).15,965 core and 18,350 discretionary foods were included. Of these, 8230 (52%) core foods and 15,947 (87%) discretionary foods contained added sugar. Median (Q1, Q3) HSRs were 4.0 (3.0, 4.5) for core foods and 2.0 (1.0, 3.0) for discretionary foods. Median added sugar contents (g/100 g) were 3.3 (1.5, 5.5) for core foods and 14.6 (1.8, 37.2) for discretionary foods. Of all the nutrients used in the current HSR algorithm, total sugar had the greatest individual capacity to discriminate between core and discretionary foods; AUC 0.692 (0.686; 0.697). Added sugar alone achieved an AUC of 0.777 (0.772; 0.782). A model with all nutrients in the current HSR algorithm had an AUC of 0.817 (0.812; 0.821), which increased to 0.871 (0.867; 0.874) with inclusion of added sugar.The HSR nutrients discriminate well between core and discretionary packaged foods. However, discrimination was improved when added sugar was also included. These data argue for inclusion of added sugar in an updated HSR algorithm and declaration of added sugar as part of mandatory nutrient declarations.

Dataset Information

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?

Publications

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?

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