Evidence map›Paper›PMID 35889764›Full record

ArticleNutrients2022

Development of Food Group Tree-Based Analysis and Its Association with Non-Alcoholic Fatty Liver Disease (NAFLD) and Co-Morbidities in a South Indian Population: A Large Case-Control Study.

Amrita Vijay, Amina Al-Awadi, Jane Chalmers, Leena Balakumaran, Jane I Grove, Ana M Valdes, Moira A Taylor, Kotacherry T Shenoy, Guruprasad P Aithal

Open access · goldAbstract 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 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
1.6field-weighted citation impact, top 17% 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

6 citing papers in PubMed, 1 synthesis or guideline pooled it, 12 citations in OpenAlex.

  1. Pooled it
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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

9 authors at 2 institutions in 1 country.

Amrita VijayInflammation, Injury and Recovery Sciences, School of Medicine, University of Nottingham, Nottingham NG7 2UH, UK.
Amina Al-AwadiNational Institute for Health Research (NIHR) Nottingham Biomedical Research Centre, Nottingham University Hospitals NHS Trust and the University of Nottingham, Nottingham NG7 2UH, UK.ORCID 0000-0003-4333-7319
Jane ChalmersNational Institute for Health Research (NIHR) Nottingham Biomedical Research Centre, Nottingham University Hospitals NHS Trust and the University of Nottingham, Nottingham NG7 2UH, UK.ORCID 0000-0001-6301-0669
Leena BalakumaranPopulation Health Research Institute (PHRI), Trivandrum, Kerala 695011, India.
Jane I GroveNational Institute for Health Research (NIHR) Nottingham Biomedical Research Centre, Nottingham University Hospitals NHS Trust and the University of Nottingham, Nottingham NG7 2UH, UK.ORCID 0000-0002-9950-7201
Ana M ValdesInflammation, Injury and Recovery Sciences, School of Medicine, University of Nottingham, Nottingham NG7 2UH, UK.
Moira A TaylorSchool of Life Sciences, Faculty of Medicine and Health Sciences, University of Nottingham, Nottingham NG7 2UH, UK.ORCID 0000-0003-4100-8343
Kotacherry T ShenoyPopulation Health Research Institute (PHRI), Trivandrum, Kerala 695011, India.
Guruprasad P AithalNational Institute for Health Research (NIHR) Nottingham Biomedical Research Centre, Nottingham University Hospitals NHS Trust and the University of Nottingham, Nottingham NG7 2UH, UK.ORCID 0000-0003-3924-4830
Nottingham University Hospitals NHS Trust · GBUniversity of Nottingham · GB

Funding

NIHR Nottingham Biomedical Research Centre BRC-1215-20003
6 · The paper itself

Abstract

backgroundNon-alcoholic fatty liver disease (NAFLD) is a global problem growing in parallel to the epidemics of obesity and diabetes, with South Asians being particularly susceptible. Nutrition and behaviour are important modifiers of the disease; however, studies to date have only described dietary patterns and nutrients associated with susceptibility to NAFLD.

methodsThis cross-sectional case-control study included 993 NAFLD patients and 973 healthy controls from Trivandrum (India). Dietary data was collected using a locally validated food frequency questionnaire. A tree-based classification categorised 2165 ingredients into three levels (food groups, sub-types, and cooking methods) and intakes were associated with clinical outcomes.

resultsNAFLD patients had significantly higher consumption of refined rice, animal fat, red meat, refined sugar, and fried foods, and had lower consumption of vegetables, pulses, nuts, seeds, and milk compared to controls. The consumption of red meat, animal fat, nuts, and refined rice was positively associated with NAFLD diagnosis and the presence of fibrosis, whereas consumption of leafy vegetables, fruits, and dried pulses was negatively associated. Fried food consumption was positively associated with NAFLD, whilst boiled food consumption had a negative association. Increased consumption of animal fats was associated with diabetes, hypertension, and cardiovascular outcomes among those with NAFLD, whereas consumption of wholegrain rice was negatively associated with these clinical-related outcomes.

conclusionsThe tree-based approach provides the first comprehensive method of classifying food intakes to enable the identification of specific dietary factors associated with NAFLD and related clinical outcomes. This could inform culturally sensitive dietary guidelines to reduce risk of NAFLD development and/or its progression.

Indexed as

Non-alcoholic Fatty Liver DiseaseAnimalsCase-Control StudiesCross-Sectional StudiesDietMorbidityRisk FactorsVegetablescase-controlco-morbiditiesdietary factorsfood groupsNAFLDSouth Asians

Identifiers

PMID35889764
PMCPMC9322963
OpenAlexW4285010525

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.