Evidence map›Paper›PMID 40999694›Full record

ArticleThe British journal of nutrition2025

Validation of a screener to assess ultra-processed food consumption in the adult Indian population: the Nova-UPF Screener (for India).

Suparna Ghosh-Jerath, Srishti Mediratta, Gaurika Kumar, Sahiba Kohli, Fernanda H Marrocos-Leite, Neha Khandpur, K Srinath Reddy

Abstract readValidation Study
PubMed Full text at PMC Publisher
In one paragraph

Article in The British journal of nutrition, 2025. 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
  2. Article
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.

Suparna Ghosh-JerathThe George Institute for Global Healthhttps://ror.org/03s4x4e93, New Delhi, India.ORCID https://orcid.org/0000-0002-2229-4455
Srishti MedirattaLady Irwin College, University of Delhi, New Delhi, India.ORCID https://orcid.org/0000-0002-6978-4443
Gaurika KumarThe George Institute for Global Healthhttps://ror.org/03s4x4e93, New Delhi, India.
Sahiba KohliThe George Institute for Global Healthhttps://ror.org/03s4x4e93, New Delhi, India.ORCID https://orcid.org/0000-0003-4281-6772
Fernanda H Marrocos-LeiteCenter for Epidemiological Research in Nutrition and Health, Faculty of Public Health, University of Sao Paulo, Sao Paulo, Brazil.
Neha KhandpurWageningen University, Wageningen, the Netherlands.
K Srinath ReddyPublic Health Foundation of India, New Delhi, India.

Funding

Gates Foundation INV-002962
6 · The paper itself

Abstract

Increasing prevalence of diet-related non-communicable diseases in India is attributed to overconsumption of energy-dense, nutrient-poor diets and ultra processed foods (UPF) may potentially contribute to this consumption pattern. Applying standard UPF definition and developing appropriate tools can better capture its consumption among Indians. This cross-sectional study aimed to validate the 'Nova-UPF Screener (for India)' and explore its potential to objectively capture UPF consumption among Indian adults. The screener, adapted in prior formative research study from a tool for Brazilian population, was subjected to content, face and concurrent criterion validation. Subject matter experts (

Indexed as

DietDiet SurveysFast FoodsFeeding BehaviorAdolescentAdultCross-Sectional StudiesFemaleFood, ProcessedHumansIndiaMaleMiddle AgedNutrition AssessmentReproducibility of ResultsSurveys and QuestionnairesBurden of diet-related non-communicable diseasesDietary assessment toolFood consumptionIndiaNova classificationNutrition surveysTool adaptationUltra-processed foodsValidation study

Identifiers

PMID40999694
PMCPMC12766108

What OpenQuestion holds

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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.