Evidence map›Paper›PMID 35406096›Full record

ArticleNutrients2022

A New Carbohydrate Food Quality Scoring System to Reflect Dietary Guidelines: An Expert Panel Report.

Adam Drewnowski, Matthieu Maillot, Yanni Papanikolaou, Julie Miller Jones, Judith Rodriguez, Joanne Slavin, Siddhartha S Angadi, Kevin B Comerford

Abstract read
In one paragraph

Article in Nutrients, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

  1. Nutrient profiling methods applied to mixed dishes and meals.Asia Pacific journal of clinical nutrition · 2026
    Review
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  10. Perspective: Potatoes, Quality Carbohydrates, and Dietary Patterns.Advances in nutrition (Bethesda, Md.) · 2024
    Article
  11. 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

8 authors.

Adam DrewnowskiCenter for Public Health Nutrition, University of Washington, Seattle, WA 98195, USA.
Matthieu MaillotMS-Nutrition, Faculté de Médecine La Timone, CEDEX 5, 13385 Marseille, France.ORCID 0000-0003-4120-0802
Yanni PapanikolaouNutritional Strategies Inc., Nutrition Research & Regulatory Affairs, Paris, ON N3L 0A3, Canada.
Julie Miller JonesEmerita, Department of Nutrition and Exercise Science, St. Catherine University, St. Paul, MN 55105, USA.
Judith RodriguezDepartment of Nutrition & Dietetics, Brooks College of Health, University of North Florida, Jacksonville, FL 32224, USA.ORCID 0000-0003-2802-9836
Joanne SlavinDepartment of Food Science and Nutrition, University of Minnesota, St. Paul, MN 55108, USA.ORCID 0000-0003-0720-5300
Siddhartha S AngadiSchool of Education and Human Development, University of Virginia, Charlottesville, VA 22904, USA.ORCID 0000-0002-2932-7926
Kevin B ComerfordOMNI Nutrition Science, Davis, CA 95616, USA.ORCID 0000-0003-0559-4824

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Existing metrics of carbohydrate food quality have been based, for the most part, on favorable fiber- and free sugar-to-carbohydrate ratios. In these metrics, higher nutritional quality carbohydrate foods are defined as those with >10% fiber and <10% free sugar per 100 g carbohydrate. Although fiber- and sugar-based metrics may help to differentiate the nutritional quality of various types of grain products, they may not aptly capture the nutritional quality of other healthy carbohydrate foods, including beans, legumes, vegetables, and fruits. Carbohydrate food quality metrics need to be applicable across these diverse food groups. This report introduces a new carbohydrate food scoring system known as a Carbohydrate Food Quality Score (CFQS), which supplements the fiber and free sugar components of previous metrics with additional dietary components of public health concern (e.g., sodium, potassium, and whole grains) as identified by the Dietary Guidelines for Americans. Two CFQS models are developed and tested in this study: one that includes four dietary components (CFQS-4: fiber, free sugars, sodium, potassium) and one that considers five dietary components (CFQS-5: fiber, free sugars, sodium, potassium, and whole grains). These models are applied to 2596 carbohydrate foods in the Food and Nutrient Database for Dietary Studies (FNDDS) 2017−2018. Consistent with past studies, the new carbohydrate food scoring system places large percentages of beans, vegetables, and fruits among the top scoring carbohydrate foods. The whole grain component, which only applies to grain foods (N = 1561), identifies ready-to-eat cereals, oatmeal, other cooked cereals, and selected whole grain breads and crackers as higher-quality carbohydrate foods. The new carbohydrate food scoring system shows a high correlation with the Nutrient Rich Food (NRF9.3) index and the Nutri-Score. Metrics of carbohydrate food quality that incorporate whole grains, potassium, and sodium, in addition to sugar and fiber, are strategically aligned with multiple 2020−2025 dietary recommendations and may therefore help with the implementation of present and future dietary guidelines.

Indexed as

Dietary FiberFabaceaeEdible GrainFood QualityHumansNutritive ValuePotassiumSodiumSugarsUnited StatesVegetablesDietary FiberPotassiumSodiumSugarscarbohydrate foodsDietary Guidelines for Americansfiberfree sugarsnutrient profilingpotassiumsodiumwhole grain

Identifiers

PMID35406096
PMCPMC9003092

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Registered trials

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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.