Evidence map›Paper›PMID 39300429›Full record

ArticleBMC medicine2024

Prepackaged foods healthiness ranking index: developing front-of-pack labeling to facilitate the assessment and validation of healthiness rankings of prepackaged foods in China.

Feiyan Wu, Yulong Qin, Dan Hou, Sasa Xie, Guanchao Zhang, Dexing Zhang, Min Yang

Abstract read
In one paragraph

Article in BMC medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
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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

7 authors.

Feiyan Wu *School of Public Health and Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, 866 Yuhangtang Road, Hangzhou, 310058, Zhejiang, China.
Yulong Qin *School of Design, Shanghai Jiao Tong University, Shanghai, China.
Dan HouSchool of Public Health and Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, 866 Yuhangtang Road, Hangzhou, 310058, Zhejiang, China.
Sasa XieSchool of Public Health and Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, 866 Yuhangtang Road, Hangzhou, 310058, Zhejiang, China.
Guanchao ZhangHangzhou 11th Middle School, Hangzhou, Zhejiang, China.
Dexing ZhangJockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong, China. zhangdxdaisy@cuhk.edu.hk.
Min YangSchool of Public Health and Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, 866 Yuhangtang Road, Hangzhou, 310058, Zhejiang, China. ymin36@ziu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe Medium and Long-Term Plan for the Prevention and Treatment of Chronic Diseases (2017-2025) in China has highlighted the importance of reducing fat, sodium, and sugar in foods. However, front-of-pack labeling, which enables consumers to assess the health levels of prepackaged foods, is lacking in China. In response to the Zhejiang Provincial Health Commission's request, we sought to develop a method for efficiently evaluating the health level of prepackaged foods.

methodsThrough a comprehensive literature review, we established a systematic framework: the Prepackaged Foods Healthiness Ranking Index (PHRI). We determined specific threshold values and grading criteria and conducted two rounds of Delphi survey to refine the index. Using a measurement dataset, we aimed to determine the optimal limit values for assessing the health level of prepackaged foods in real-world settings.

resultsAfter two rounds of Delphi surveys, the PHRI underwent multiple revisions until consensus among experts was reached. The final decision regarding the upper limit values set 30% Nutrient Reference Values as the limit for solid foods and 15% Nutrient Reference Values for liquid foods. The calculation of PHRI values was successfully implemented with the dataset, in accord with current nutrition awareness and real-world conditions.

conclusionsThe PHRI provides a valuable tool for assessing the healthiness of prepackaged foods. This front-of-pack labeling system provides a convenient method for evaluating the nutritional quality of prepackaged foods. Ultimately, the PHRI has the potential to contribute to advancements in health policy, practice, and education in China.

Indexed as

Delphi TechniqueFood LabelingChinaFood PackagingHumansNutritive ValueDelphi methodFOPLHealth rankPHRIPrepackaged food

Identifiers

PMID39300429
PMCPMC11414037

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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.