Evidence map›Paper›PMID 35657786›Full record

ArticlePloS one2022

Comparing different metabolic indexes to predict type 2 diabetes mellitus in a five years follow-up cohort: The Baependi Heart Study.

Camila Maciel de Oliveira, Jessica Leticia Pavani, Chunyu Liu, Mercedes Balcells, Robson Capasso, Rafael de Oliveira Alvim, Carlos Alberto Mourão-Júnior, José Eduardo Krieger, Alexandre Costa Pereira

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
0.6field-weighted citation impact, top 32% 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

3 citing papers in PubMed, 1 synthesis or guideline pooled it, 5 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. 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

9 authors at 6 institutions in 4 countries.

Camila Maciel de OliveiraStanford University School of Medicine, Stanford, California, United States of America.ORCID 0000-0001-6823-7395
Jessica Leticia PavaniDepartment of Statistics, Pontificia Universidad Católica de Chile, Santiago, Chile.ORCID 0000-0001-9613-2400
Chunyu LiuFramingham Heart Study, Framingham, Massachusetts, United States of America.
Mercedes BalcellsInstitute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.
Robson CapassoStanford University School of Medicine, Stanford, California, United States of America.
Rafael de Oliveira AlvimLaboratory of Genetics and Molecular Cardiology, Heart Institute (InCor), University of São Paulo Medical School, São Paulo, Brazil.
Carlos Alberto Mourão-JúniorDepartment of Physiology, Federal University of Juiz de Fora, Juiz de Fora, Brazil.ORCID 0000-0001-7199-5365
José Eduardo KriegerLaboratory of Genetics and Molecular Cardiology, Heart Institute (InCor), University of São Paulo Medical School, São Paulo, Brazil.
Alexandre Costa PereiraLaboratory of Genetics and Molecular Cardiology, Heart Institute (InCor), University of São Paulo Medical School, São Paulo, Brazil.
Universidade de São Paulo · BRBoston University · USInstitut Químic de Sarrià · ESPontificia Universidad Católica de Chile · CLStanford University · USUniversidade Federal de Juiz de Fora · BR

Funding

Leveraging a Unique existing Cohort to elucidate the Link between sleep and cardio-metabolic diseaseR01HL141881 · NHLBI · NORTHWESTERN UNIVERSITY AT CHICAGO · PI KNUTSON, KRISTEN · 2019 to 2022
$2.7M
NHLBI NIH HHS R01 HL141881
6 · The paper itself

Abstract

This study evaluates the association of anthropometric indexes and the incidence of type 2 diabetes mellitus (T2DM) after a 5-year follow-up. This analysis included 1091 middle-aged participants (57% women, mean age 47 ± 15 years) who were free of T2DM at baseline and attended two health examinations cycles [cycle 1 (2005-2006) and cycle 2 (2010-2013)]. As expected, the participants who developed T2DM after five years (3.8%) had the worst metabolic profile with higher hypertension, dyslipidemia, and obesity rates. Besides, using mixed-effects logistic regression and adjustment for sex, age, and glucose, we found that one unit increase in body adiposity index (BAI) was associated with an 8% increase in their risk of developing T2DM (odds ratio [OR] = 1.08 [95% CI, 1.02-1.14]) and visceral adiposity index (VAI) was associated with a risk increase of 11% (OR = 1.11 [95% CI, 1.00-1.22]). Moreover, a one-unit increase in the triglycerides-glucose index (TyG) was associated with more than four times the risk of developing T2DM (OR = 4.27 [95% CI, 1.01-17.97]). The interquartile range odds ratio for the continuous predictors showed that TyG had the best discriminating performance. However, when any of them were additionally adjusted for waist circumference (WC) or even body mass index (BMI), all adiposity indexes lost the effect in predicting T2DM. In conclusion, TyG had the most substantial predictive power among all three indexes. However, neither BAI, VAI, nor TyG were superior to WC or BMI for predicting the risk of developing T2DM in a middle-aged normoglycemic sample in this rural Brazilian population.

Indexed as

Diabetes Mellitus, Type 2AdiposityAdultBody Mass IndexFemaleFollow-Up StudiesGlucoseHumansMaleMiddle AgedObesityObesity, AbdominalRisk FactorsTriglyceridesWaist CircumferenceGlucoseTriglycerides

Identifiers

PMID35657786
PMCPMC9165883
OpenAlexW4281689445

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.