Evidence map›Paper›PMID 38495314›Full record

ArticleLancet regional health. Americas2024

A policy approach to identifying food and beverage products that are ultra-processed and high in added salt, sugar and saturated fat in the United States: a cross-sectional analysis of packaged foods.

Barry M Popkin, Donna R Miles, Lindsey Smith Taillie, Elizabeth K Dunford

Open access · goldAbstract read
In one paragraph

Article in Lancet regional health. Americas, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.

0numbers the graph read from it
0cells of the map it votes in
37citing papers in PubMed
18.5field-weighted citation impact, top 1% of its field
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

37 citing papers in PubMed, 34 citations in OpenAlex.

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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

4 authors at 1 institution in 2 countries.

Barry M PopkinDepartment of Nutrition, Gillings Global School of Public Health, The University of North Carolina at Chapel Hill, USA.
Donna R MilesCarolina Population Center, The University of North Carolina at Chapel Hill, USA.
Lindsey Smith TaillieDepartment of Nutrition, Gillings Global School of Public Health, The University of North Carolina at Chapel Hill, USA.
Elizabeth K DunfordDepartment of Nutrition, Gillings Global School of Public Health, The University of North Carolina at Chapel Hill, USA.
University of North Carolina at Chapel Hill · US

Funding

UNIV OF NORTH CAROLINA CLINICAL NUTRITION RESEARCH UNITP30DK056350 · NIDDK · UNIV OF NORTH CAROLINA CHAPEL HILL · PI SUSAN M. SMITH · 1999 to 2026
$31.6M
NIDDK NIH HHS P30 DK056350
6 · The paper itself

Abstract

Background: Governments globally aim to reduce the intake of unhealthy foods. Many policies exist that aim to address foods high in saturated fat, salt and sugar (HFSS) but the identification of ultra-processed foods (UPF) have presented a greater challenge due to the lack of an appropriate policy definition. To support policymakers, we provide approaches that can support governments to identify both HFSS foods and UPFs. Methods: Four approaches combining elements of UPF definitions (i.e., presence of additives) and HFSS definitions were compared attempting to simplify and standardize the identification of less healthy products. Nationally representative food purchase data from NielsenIQ linked with nutrition facts label data were used to examine the mean proportion of product volume purchased by US households to be targeted. Differences between approaches were examined using Student Findings: In 2020, 50% of 33,054,687 products purchased by US households were considered UPFs (65% of foods and 38% of beverages) and 43% HFSS (65% of foods and 26% of beverages), however there was not 100% agreement between the two definitions (P < 0.0001). By starting with HFSS criteria and adding elements of UPF (colors and flavors), we were able to provide a method with 100% agreement between the identification of UPFs and HFSS products. Interpretation: Results demonstrated how combining HFSS criteria with UPF criteria can be used to identify less healthy foods and ensure policymakers have both a simple and accurate method to target products for policy intervention. Funding: Bloomberg Philanthropies and the Global Food Research Program of UNC-Chapel Hill provided funds.

Indexed as

AdditivesAnd sugar (HFSS)High in added saturated fatNonnutritive sweeteners (NNS)SodiumUltra-processed foods (UPF)

Identifiers

PMID38495314
PMCPMC10943474
OpenAlexW4392611796

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.