Evidence map›Paper›PMID 38974584›Full record

ArticlePreventive nutrition and food science2024

Health Star Rating of Nonalcoholic, Packaged, and Ready-to-Drink Beverages in Türkiye: A Decision Tree Model Study.

Aylin Bayındır Gümüş, Murat Açık, Sevinç Eşer Durmaz

Abstract read
In one paragraph

Article in Preventive nutrition and food science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Aylin Bayındır GümüşFirst and Emergency Aid Program, Vocational School of Health Services, Kırıkkale University, Kırıkkale 71450, Türkiye.ORCID https://orcid.org/0000-0002-1311-2429
Murat AçıkDepartment of Nutrition and Dietetics, Faculty of Health Sciences, Fırat University, Elazığ 23200, Türkiye.ORCID https://orcid.org/0000-0002-3104-6306
Sevinç Eşer DurmazDepartment of Nutrition and Dietetics, Faculty of Health Sciences, Kırıkkale University, Kırıkkale 71450, Türkiye.ORCID https://orcid.org/0000-0002-2425-1715

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aimed to compare the nutritional quality of beverages sold in Türkiye according to their labeling profiles. A total of 304 nonalcoholic beverages sold in supermarkets and online markets with the highest market capacity in Türkiye were included. Milk and dairy products, sports drinks, and beverages for children were excluded. The health star rating (HSR) was used to assess the nutritional quality of beverages. The nutritional quality of beverages was evaluated using a decision tree model according to the HSR score based on the variables presented on the beverage label. Moreover, confusion matrix tests were used to test the model's accuracy. The mean HSR score of beverages was 2.6±1.9, of which 30.2% were in the healthy category (HSR≥3.5). Fermented and 100% fruit juice beverages had the highest mean HSR scores. According to the decision tree model of the training set, the predictors of HSR quality score, in order of importance, were as follows: added sugar (46%), sweetener (28%), additives (19%), fructose-glucose syrup (4%), and caffeine (3%). In the test set, the accuracy rate and F1 score were 0.90 and 0.82, respectively, suggesting that the prediction performance of our model had the perfect fit. According to the HSR classification, most beverages were found to be unhealthy. Thus, they increase the risk of the development of obesity and other diseases because of their easy consumption. The decision tree learning algorithm could guide the population to choose healthy beverages based on their labeling information.

Indexed as

beveragesfood qualitynutrient intakenutritive valuesugar-sweetened beverages

Identifiers

PMID38974584
PMCPMC11223921

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.