Evidence map›Paper›PMID 34916558›Full record

ArticleScientific reports2021

A family history of type 2 diabetes as a predictor of fatty liver disease in diabetes-free individuals with excessive body weight.

Giovanni De Pergola, Fabio Castellana, Roberta Zupo, Sara De Nucci, Francesco Panza, Marco Castellana, Luisa Lampignano, Martina Di Chito, Vincenzo Triggiani, Rodolfo Sardone and 1 more

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.7field-weighted citation impact, top 16% 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

8 citing papers in PubMed, 11 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

11 authors at 2 institutions in 1 country.

Giovanni De Pergola *Unit of Geriatrics and Internal Medicine, National Institute of Gastroenterology "Saverio de Bellis", Research Hospital, 70013, Castellana Grotte, BA, Italy. giovanni.depergola@irccsdebellis.it.
Fabio Castellana *Unit of Data Sciences and Technology Innovation for Population Health, National Institute of Gastroenterology "Saverio de Bellis", Research Hospital, 70013, Castellana Grotte, BA, Italy.
Roberta ZupoUnit of Data Sciences and Technology Innovation for Population Health, National Institute of Gastroenterology "Saverio de Bellis", Research Hospital, 70013, Castellana Grotte, BA, Italy.
Sara De NucciUnit of Data Sciences and Technology Innovation for Population Health, National Institute of Gastroenterology "Saverio de Bellis", Research Hospital, 70013, Castellana Grotte, BA, Italy.
Francesco PanzaUnit of Data Sciences and Technology Innovation for Population Health, National Institute of Gastroenterology "Saverio de Bellis", Research Hospital, 70013, Castellana Grotte, BA, Italy.
Marco CastellanaUnit of Data Sciences and Technology Innovation for Population Health, National Institute of Gastroenterology "Saverio de Bellis", Research Hospital, 70013, Castellana Grotte, BA, Italy.
Luisa LampignanoUnit of Data Sciences and Technology Innovation for Population Health, National Institute of Gastroenterology "Saverio de Bellis", Research Hospital, 70013, Castellana Grotte, BA, Italy.
Martina Di ChitoUnit of Geriatrics and Internal Medicine, National Institute of Gastroenterology "Saverio de Bellis", Research Hospital, 70013, Castellana Grotte, BA, Italy.
Vincenzo TriggianiSection of Internal Medicine, Geriatrics, Endocrinology, and Rare Disease, Interdisciplinary Department of Medicine, School of Medicine, University of Bari, 70124, Bari, Italy.
Rodolfo SardoneUnit of Data Sciences and Technology Innovation for Population Health, National Institute of Gastroenterology "Saverio de Bellis", Research Hospital, 70013, Castellana Grotte, BA, Italy.
Gianluigi GiannelliScientific Direction, National Institute of Gastroenterology "Saverio de Bellis", Research Hospital, 70013, Castellana Grotte, BA, Italy.
Gastroenterology Hospital "Saverio de Bellis" · ITUniversity of Bari Aldo Moro · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Comprehensive screening for non-alcoholic fatty liver disease (NAFLD) may help prompt clinical management of fatty liver disease. A family history, especially of diabetes, has been little studied as a predictor for NAFLD. We characterized the cross-sectional relationship between a family history of type 2 diabetes (FHT2D) and NAFLD probability in 1185 diabetes-free Apulian (Southern-Italy) subjects aged > 20 years with overweight or obesity not receiving any drug or supplementation. Clinical data and routine biochemistry were analysed. NAFLD probability was defined using the fatty liver index (FLI). A first-degree FHT2D was assessed by interviewing subjects and assigning a score of 0, 1, or 2 if none, only one, or both parents were affected by type 2 diabetes mellitus (T2DM). Our study population featured most females (70.9%, N = 840), and 48.4% (N = 574) of the sample had first-degree FHT2D. After dividing the sample by a FHT2D, we found a higher BMI, Waist Circumference (WC), and diastolic blood pressure shared by FHT2D subjects; they also showed altered key markers of glucose homeostasis, higher triglyceride levels, and worse liver function. FLI scores were significantly lower in subjects without a first-degree FHT2D. After running logistic regression models, a FHT2D was significantly associated with the NAFLD probability, even adjusting for major confounders and stratifying by age (under and over 40 years of age). A FHT2D led to an almost twofold higher probability of NAFLD, regardless of confounding factors (OR 2.17, 95% CI 1.63 to 2.89). A first-degree FHT2D acts as an independent determinant of NAFLD in excess weight phenotypes, regardless of the age group (younger or older than 40 years). A NAFLD risk assessment within multidimensional screening might be useful in excess weight subjects reporting FHT2D even in the absence of diabetes.

Indexed as

Medical History TakingAdultAgedBody Mass IndexCross-Sectional StudiesDiabetes Mellitus, Type 2FemaleForecastingHumansItalyLogistic ModelsMaleMiddle AgedNon-alcoholic Fatty Liver DiseaseOverweightProbability

Identifiers

PMID34916558
PMCPMC8677812
OpenAlexW4200105622

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.