Dataset Information

Evaluation of Alignment between the Health Claims Nutrient Profiling Scoring Criterion (NPSC) and the Health Star Rating (HSR) Nutrient Profiling Models.

ABSTRACT: 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.

SUBMITTER: Dunford EK

PROVIDER: S-EPMC6115993 | biostudies-literature |

REPOSITORIES: biostudies-literature

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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: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.

Project description:ImportanceThe Centers for Medicare & Medicaid Services' Five-Star Quality Rating System combines results from nursing home recertification surveys and complaint investigations into a single indicator for health inspections. This combination may mask complaint investigation results.ObjectiveTo construct and compare star ratings specific to recertification surveys and specific to complaint investigations to discern whether they provide different information.Design, setting, and participantsIn this quality improvement study, the Nursing Home Compare Five-Star Quality Rating System was used to calculate three 5-star ratings: 1 overall health inspection rating combining recertification survey scores and complaint investigation scores, 1 using only recertification scores, and 1 using only complaint investigation scores. The study included US nursing homes. The sample calculated star ratings for nursing homes in November 2017. This sample included all whose most recent recertification surveys occurred in 2016 up to and including November 2017, and those with 36 months of data from the ASPEN Complaints/Incidents Tracking System and the Certification and Survey Provider Enhanced Reports. Data analyses were completed on different days in 2022, depending on which questions were being addressed.Main outcomes and measuresComparison of the 3 star rating distributions. The recertification survey and complaint investigation star ratings were compared with respect to the overall health investigation rating. The recertification and complaint star ratings were cross-tabulated.ResultsAmong the 15 499 nursing homes, 19.8% had 1 overall health inspection star, 23.2% had 2, 23.2% had 3, 23.2% had 4, and 9.8% had 5 overall health inspection stars. Most had the same overall and recertification star ratings; for example, 79.4% had 5 overall stars and 5 recertification survey stars. However, overall and complaint-based star ratings were discordant, with a relatively large proportion of nursing homes (25.7%) having no complaint deficiencies and therefore high star ratings.Conclusions and relevanceIn this quality improvement study assessing the 2 components of the Five-Star Quality Rating System, results of recertification surveys were largely similar to health inspection star ratings. However, recertification survey scores differed from complaint inspection scores, suggesting health inspection ratings may not reflect consumers' views of care, services, or other valued amenities. A complaint-focused metric may have utility. However, research is needed concerning the many nursing homes with no or very few complaint deficiencies.

Dataset Information

Evaluation of Alignment between the Health Claims Nutrient Profiling Scoring Criterion (NPSC) and the Health Star Rating (HSR) Nutrient Profiling Models.

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