Evidence map›Paper›PMID 35073909›Full record

Trial reportThe international journal of behavioral nutrition and physical activity2022

Integrative development of a short screening questionnaire of highly processed food consumption (sQ-HPF).

Celia Martinez-Perez, Lidia Daimiel, Cristina Climent-Mainar, Miguel Ángel Martínez-González, Jordi Salas-Salvadó, Dolores Corella, Helmut Schröder, Jose Alfredo Martinez, Ángel M Alonso-Gómez, Julia Wärnberg and 39 more

Registry-linked trialOpen access · goldAbstract readRandomized Controlled Trial
In one paragraph

Trial report in The international journal of behavioral nutrition and physical activity, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07103811 (The Relationship Between Social Media Use, Food Craving and Ultra-Processed Food Consumption in University Students), which is not on this map. Cited by 34 papers.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed
6.4field-weighted citation impact, top 3% 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.

NCT07103811 recruitingnot on this mapstarted 2025, after this paper: background citation

The Relationship Between Social Media Use, Food Craving and Ultra-Processed Food Consumption in University Students

TypeobservationalSponsorAtılım UniversityRan2025 to 2025Enrolled150ConditionsFood Craving, Ultra Processed Food, Social Media
3 · Its place in the literature

Who cites it

34 citing papers in PubMed, 41 citations in OpenAlex.

  1. Trial
  2. Article
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  4. Review
  5. Article
  6. The dynamic spectrum of steatotic liver disease: the global perspective.Nature reviews. Gastroenterology & hepatology · 2026
    Review
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  9. Observational
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  18. Observational
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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

49 authors at 13 institutions in 2 countries.

Celia Martinez-PerezNutritional Genomics and Epigenomics Group, Precision Nutrition and Obesity Program, IMDEA Food, CEI UAM + CSIC, Ctra. Cantoblanco, 8, 28049, Madrid, Spain.
Lidia DaimielNutritional Genomics and Epigenomics Group, Precision Nutrition and Obesity Program, IMDEA Food, CEI UAM + CSIC, Ctra. Cantoblanco, 8, 28049, Madrid, Spain. lidia.daimiel@imdea.org.ORCID 0000-0001-9898-6629
Cristina Climent-MainarNutritional Genomics and Epigenomics Group, Precision Nutrition and Obesity Program, IMDEA Food, CEI UAM + CSIC, Ctra. Cantoblanco, 8, 28049, Madrid, Spain.
Miguel Ángel Martínez-GonzálezBiomedical Research Centre for Obesity Physiopathology and Nutrition Network (CIBEROBN), Instituto de Salud Carlos III (ISCIII), 28029, Madrid, Spain.
Jordi Salas-SalvadóBiomedical Research Centre for Obesity Physiopathology and Nutrition Network (CIBEROBN), Instituto de Salud Carlos III (ISCIII), 28029, Madrid, Spain.
Dolores CorellaBiomedical Research Centre for Obesity Physiopathology and Nutrition Network (CIBEROBN), Instituto de Salud Carlos III (ISCIII), 28029, Madrid, Spain.
Helmut SchröderCardiovascular Risk and Nutrition Research Group (CARIN), Hospital del Mar Medical Research Institute (IMIM), 08003, Barcelona, Spain.
Jose Alfredo MartinezBiomedical Research Centre for Obesity Physiopathology and Nutrition Network (CIBEROBN), Instituto de Salud Carlos III (ISCIII), 28029, Madrid, Spain.
Ángel M Alonso-GómezBiomedical Research Centre for Obesity Physiopathology and Nutrition Network (CIBEROBN), Instituto de Salud Carlos III (ISCIII), 28029, Madrid, Spain.
Julia WärnbergBiomedical Research Centre for Obesity Physiopathology and Nutrition Network (CIBEROBN), Instituto de Salud Carlos III (ISCIII), 28029, Madrid, Spain.
Jesús VioqueCentro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III, 28029, Madrid, Spain.
Dora RomagueraBiomedical Research Centre for Obesity Physiopathology and Nutrition Network (CIBEROBN), Instituto de Salud Carlos III (ISCIII), 28029, Madrid, Spain.
José López-MirandaBiomedical Research Centre for Obesity Physiopathology and Nutrition Network (CIBEROBN), Instituto de Salud Carlos III (ISCIII), 28029, Madrid, Spain.
Ramón EstruchBiomedical Research Centre for Obesity Physiopathology and Nutrition Network (CIBEROBN), Instituto de Salud Carlos III (ISCIII), 28029, Madrid, Spain.
Francisco J TinahonesBiomedical Research Centre for Obesity Physiopathology and Nutrition Network (CIBEROBN), Instituto de Salud Carlos III (ISCIII), 28029, Madrid, Spain.
José LapetraBiomedical Research Centre for Obesity Physiopathology and Nutrition Network (CIBEROBN), Instituto de Salud Carlos III (ISCIII), 28029, Madrid, Spain.
Lluis Serra-MajemBiomedical Research Centre for Obesity Physiopathology and Nutrition Network (CIBEROBN), Instituto de Salud Carlos III (ISCIII), 28029, Madrid, Spain.
Aurora Bueno-CavanillasCentro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III, 28029, Madrid, Spain.
Josep A TurBiomedical Research Centre for Obesity Physiopathology and Nutrition Network (CIBEROBN), Instituto de Salud Carlos III (ISCIII), 28029, Madrid, Spain.
Vicente Martín SánchezCentro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III, 28029, Madrid, Spain.
Xavier PintóBiomedical Research Centre for Obesity Physiopathology and Nutrition Network (CIBEROBN), Instituto de Salud Carlos III (ISCIII), 28029, Madrid, Spain.
Miguel Delgado-RodríguezCentro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III, 28029, Madrid, Spain.
Pilar Matía-MartínDepartment of Endocrinology and Nutrition, Instituto de Investigación Sanitaria Hospital Clínico San Carlos (IdISSC), 28040, Madrid, Spain.
Josep VidalBiomedical Research Centre for Diabetes and Metabolic Diseases Network (CIBERDEM), Instituto de Salud Carlos III (ISCIII), 28029, Madrid, Spain.
Clotilde VázquezBiomedical Research Centre for Obesity Physiopathology and Nutrition Network (CIBEROBN), Instituto de Salud Carlos III (ISCIII), 28029, Madrid, Spain.
Emilio RosBiomedical Research Centre for Obesity Physiopathology and Nutrition Network (CIBEROBN), Instituto de Salud Carlos III (ISCIII), 28029, Madrid, Spain.
Javier BasterraDepartment of Preventive Medicine and Public Health, University of Navarra, IdiSNA, 31009, Pamplona, Spain.
Nancy BabioBiomedical Research Centre for Obesity Physiopathology and Nutrition Network (CIBEROBN), Instituto de Salud Carlos III (ISCIII), 28029, Madrid, Spain.
Patricia Guillem-SaizBiomedical Research Centre for Obesity Physiopathology and Nutrition Network (CIBEROBN), Instituto de Salud Carlos III (ISCIII), 28029, Madrid, Spain.
María Dolores ZomeñoCardiovascular Risk and Nutrition Research Group (CARIN), Hospital del Mar Medical Research Institute (IMIM), 08003, Barcelona, Spain.
Itziar AbeteBiomedical Research Centre for Obesity Physiopathology and Nutrition Network (CIBEROBN), Instituto de Salud Carlos III (ISCIII), 28029, Madrid, Spain.
Jessica Vaquero-LunaBiomedical Research Centre for Obesity Physiopathology and Nutrition Network (CIBEROBN), Instituto de Salud Carlos III (ISCIII), 28029, Madrid, Spain.
Francisco Javier Barón-LópezDepartment of Public Health, University of Málaga, Instituto de Investigación Biomédica de Málaga (IBIMA), 29016, Málaga, Spain.
Sandra Gonzalez-PalaciosCentro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III, 28029, Madrid, Spain.
Jadwiga KoniecznaBiomedical Research Centre for Obesity Physiopathology and Nutrition Network (CIBEROBN), Instituto de Salud Carlos III (ISCIII), 28029, Madrid, Spain.
Antonio Garcia-RiosBiomedical Research Centre for Obesity Physiopathology and Nutrition Network (CIBEROBN), Instituto de Salud Carlos III (ISCIII), 28029, Madrid, Spain.
María Rosa Bernal-LópezInternal Medicine Department, Regional University Hospital of Málaga, Instituto de Investigación Biomédica de Málaga (IBIMA), 29010, Málaga, Spain.
José Manuel Santos-LozanoBiomedical Research Centre for Obesity Physiopathology and Nutrition Network (CIBEROBN), Instituto de Salud Carlos III (ISCIII), 28029, Madrid, Spain.
Maira Bes-RastrolloBiomedical Research Centre for Obesity Physiopathology and Nutrition Network (CIBEROBN), Instituto de Salud Carlos III (ISCIII), 28029, Madrid, Spain.
Nadine KhouryBiomedical Research Centre for Obesity Physiopathology and Nutrition Network (CIBEROBN), Instituto de Salud Carlos III (ISCIII), 28029, Madrid, Spain.
Carmen SaizBiomedical Research Centre for Obesity Physiopathology and Nutrition Network (CIBEROBN), Instituto de Salud Carlos III (ISCIII), 28029, Madrid, Spain.
Karla Alejandra Pérez-VegaCardiovascular Risk and Nutrition Research Group (CARIN), Hospital del Mar Medical Research Institute (IMIM), 08003, Barcelona, Spain.
María Angeles ZuletBiomedical Research Centre for Obesity Physiopathology and Nutrition Network (CIBEROBN), Instituto de Salud Carlos III (ISCIII), 28029, Madrid, Spain.
Lucas Tojal-SierraBiomedical Research Centre for Obesity Physiopathology and Nutrition Network (CIBEROBN), Instituto de Salud Carlos III (ISCIII), 28029, Madrid, Spain.
Zenaida Vázquez RuizBiomedical Research Centre for Obesity Physiopathology and Nutrition Network (CIBEROBN), Instituto de Salud Carlos III (ISCIII), 28029, Madrid, Spain.
Maria Angeles MartinezBiomedical Research Centre for Obesity Physiopathology and Nutrition Network (CIBEROBN), Instituto de Salud Carlos III (ISCIII), 28029, Madrid, Spain.
Mireia MalcampoCardiovascular Risk and Nutrition Research Group (CARIN), Hospital del Mar Medical Research Institute (IMIM), 08003, Barcelona, Spain.
José M OrdovásNutritional Genomics and Epigenomics Group, Precision Nutrition and Obesity Program, IMDEA Food, CEI UAM + CSIC, Ctra. Cantoblanco, 8, 28049, Madrid, Spain.
Rodrigo San-CristobalCardiometabolic Nutrition Group, IMDEA Food, CEI UAM + CSIC, 28049, Madrid, Spain.
Instituto de Salud Carlos III · ESMadrid Institute for Advanced Studies · ESHospital Del Mar · ESUniversitat de València · ESUniversity of the Basque Country · ESInstituto de Investigación Biomédica de Málaga · ESUniversity of Alicante · ESComplejo Hospitalario de Navarra · ESHarvard University · USHospital Universitario Insular de Gran Canaria · ESInstituto de Investigación Sanitaria del Hospital Clínico San Carlos · ESUniversidad de Granada · ESUniversidad de Jaén · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRecent lifestyle changes include increased consumption of highly processed foods (HPF), which has been associated with an increased risk of non-communicable diseases (NCDs). However, nutritional information relies on the estimation of HPF consumption from food-frequency questionnaires (FFQ) that are not explicitly developed for this purpose. We aimed to develop a short screening questionnaire of HPF consumption (sQ-HPF) that integrates criteria from the existing food classification systems.

methodsData from 4400 participants (48.1% female and 51.9% male, 64.9 ± 4.9 years) of the Spanish PREDIMED-Plus ("PREvention with MEDiterranean DIet") trial were used for this analysis. Items from the FFQ were classified according to four main food processing-based classification systems (NOVA, IARC, IFIC and UNC). Participants were classified into tertiles of HPF consumption according to each system. Using binomial logistic regression, food groups associated with agreement in the highest tertile for at least two classification systems were chosen as items for the questionnaire. ROC analysis was used to determine cut-off points for the frequency of consumption of each item, from which a score was calculated. Internal consistency of the questionnaire was assessed through exploratory factor analysis (EFA) and Cronbach's analysis, and agreement with the four classifications was assessed with weighted kappa coefficients.

resultsRegression analysis identified 14 food groups (items) associated with high HPF consumption for at least two classification systems. EFA showed that items were representative contributors of a single underlying factor, the "HPF dietary pattern" (factor loadings around 0.2). We constructed a questionnaire asking about the frequency of consumption of those items. The threshold frequency of consumption was selected using ROC analysis. Comparison of the four classification systems and the sQ-HPF showed a fair to high agreement. Significant changes in lifestyle characteristics were detected across tertiles of the sQ-HPF score. Longitudinal changes in HPF consumption were also detected by the sQ-HPF, concordantly with existing classification systems.

conclusionsWe developed a practical tool to measure HPF consumption, the sQ-HPF. This may be a valuable instrument to study its relationship with NCDs.

trial registrationRetrospectively registered at the International Standard Randomized Controlled Trial Registry ( ISRCTN89898870 ) on July 24, 2014.

Indexed as

Diet, MediterraneanNoncommunicable DiseasesDietFast FoodsFemaleFood HandlingHumansMaleSurveys and QuestionnairesFood processing-based classificationHighly processed foodNOVAPREDIMED-PlusQuestionnaireUltra-processed food

Identifiers

PMID35073909
PMCPMC8785596
OpenAlexW4206990564

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Registered trials

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.