Evidence map›Paper›PMID 33222702›Full record

ArticleThe British journal of nutrition2021

Characterising percentage energy from ultra-processed foods by participant demographics, diet quality and diet cost: findings from the Seattle Obesity Study (SOS) III.

Shilpi Gupta, Chelsea M Rose, James Buszkiewicz, Linda K Ko, Jin Mou, Andrea Cook, Anju Aggarwal, Adam Drewnowski

Abstract read
In one paragraph

Article in The British journal of nutrition, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed, 2 pooled it
–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

24 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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  13. Ultra-processed foods and food additives in gut health and disease.Nature reviews. Gastroenterology & hepatology · 2024
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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.

Shilpi GuptaCenter for Public Health Nutrition, Department of Epidemiology, University of Washington, Seattle, WA98105, USA.ORCID 0000-0002-4285-1749
Chelsea M RoseCenter for Public Health Nutrition, Department of Epidemiology, University of Washington, Seattle, WA98105, USA.
James BuszkiewiczCenter for Public Health Nutrition, Department of Epidemiology, University of Washington, Seattle, WA98105, USA.
Linda K KoDivision of Public Health Sciences, Department of Cancer Prevention, Fred Hutchinson Cancer Research Center, Seattle, WA98109, USA.
Jin MouMultiCare Institute for Research & Innovation, Tacoma, WA98405, USA.ORCID 0000-0001-8350-3292
Andrea CookBiostatistics Unit, Kaiser Permanente Washington Health Research Institute, Seattle, WA98101, USA.
Anju AggarwalCenter for Public Health Nutrition, Department of Epidemiology, University of Washington, Seattle, WA98105, USA.
Adam DrewnowskiCenter for Public Health Nutrition, Department of Epidemiology, University of Washington, Seattle, WA98105, USA.

Funding

Food Environment, Diet Quality and Disparities in ObesityR01DK076608 · NIDDK · UNIVERSITY OF WASHINGTON · PI DREWNOWSKI, ADAM · 2008 to 2019
$6.3M
NIDDK NIH HHS R01 DK076608
6 · The paper itself

Abstract

Higher consumption of 'ultra-processed' (UP) foods has been linked to adverse health outcomes. The present paper aims to characterise percentage energy from UP foods by participant socio-economic status (SES), diet quality, self-reported food expenditure and energy-adjusted diet cost. Participants in the population-based Seattle Obesity Study III (n 755) conducted in WA in 2016-2017 completed socio-demographic and food expenditure surveys and the FFQ. Education and residential property values were measures of SES. Retail prices of FFQ component foods (n 378) were used to estimate individual-level diet cost. Healthy Eating Index (HEI-2015) and Nutrient Rich Food Index 9.3 (NRF9.3) were measures of diet quality. UP foods were identified following NOVA classification. Multivariable linear regressions were used to test associations between UP foods energy, socio-demographics, two estimates of food spending and diet quality measures. Higher percentage energy from UP foods was associated with higher energy density, lower HEI-2015 and NRF9.3 scores. The bottom decile of diet cost ($216·4/month) was associated with 67·5 % energy from UP foods; the top decile ($369·9/month) was associated with only 48·7 % energy from UP foods. Percentage energy from UP foods was inversely linked to lower food expenditures and diet cost. In multivariate analysis, percentage energy from UP foods was predicted by lower food expenditures, diet cost and education, adjusting for covariates. Percentage energy from UP foods was linked to lower food spending and lower SES. Efforts to reduce UP foods consumption, an increasingly common policy measure, need to take affordability, food expenditures and diet costs into account.

Indexed as

DietEnergy IntakeFast FoodsDiet, HealthyHumansSociodemographic FactorsWashingtonDiet costEnergy densityHEI-2015NRF9.3Nutrient densityResidential property valuesUltra-processed foods

Identifiers

PMID33222702
PMCPMC8340456

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LicenceCC BY
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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.