Evidence map›Paper›PMID 41776484›Full record

ArticleBMC pregnancy and childbirth2026

Comparison Of Body Mass Index (BMI), an old modality for prediction of gestational diabetes, with the new formulas such as Body Adipose Index (BAİ), Adipose Percentage and Type a Body Fat Index (ABSI): a prospective cohort study.

Burcu Bozkurt Ozdal, Atakan Tanacan, Nihan Elif Teki̇n, Esra Karatas, Ayse Altındis Bal, Sükrü Bakırcı, Ozgur Kara, Dilek Sahi̇n

Abstract readComparative Study
In one paragraph

Article in BMC pregnancy and childbirth, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

8 authors.

Burcu Bozkurt OzdalPerinatology Department, Ankara Bilkent City Hospital, Göksu Neighborhood, 5350. street. Oyak Göksu houses. A2 block floor:21 no:134 Etimesgut, Ankara, 06800, Turkey. burcu_bzkrt@hotmail.com.ORCID http://orcid.org/0009-0007-6644-3890
Atakan TanacanPerinatology Department, Ankara Bilkent City Hospital, Göksu Neighborhood, 5350. street. Oyak Göksu houses. A2 block floor:21 no:134 Etimesgut, Ankara, 06800, Turkey.ORCID http://orcid.org/0000-0001-8209-8248
Nihan Elif Teki̇nGynocology and Obstetri Department, Ankara Bilkent City Hospital, Ankara, Turkey.ORCID http://orcid.org/0009-0009-4097-4655
Esra KaratasPerinatology Department, Ankara Bilkent City Hospital, Göksu Neighborhood, 5350. street. Oyak Göksu houses. A2 block floor:21 no:134 Etimesgut, Ankara, 06800, Turkey.ORCID http://orcid.org/0000-0003-3474-2398
Ayse Altındis Bal, Ankara, Turkey.ORCID http://orcid.org/0009-0003-3471-8205
Sükrü BakırcıPerinatology Department, Ankara Bilkent City Hospital, Göksu Neighborhood, 5350. street. Oyak Göksu houses. A2 block floor:21 no:134 Etimesgut, Ankara, 06800, Turkey.ORCID http://orcid.org/0000-0002-6007-965X
Ozgur KaraPerinatology Department, Ankara Bilkent City Hospital, Göksu Neighborhood, 5350. street. Oyak Göksu houses. A2 block floor:21 no:134 Etimesgut, Ankara, 06800, Turkey.ORCID http://orcid.org/0000-0002-4204-0014
Dilek Sahi̇nPerinatology Department, Ankara Bilkent City Hospital, Göksu Neighborhood, 5350. street. Oyak Göksu houses. A2 block floor:21 no:134 Etimesgut, Ankara, 06800, Turkey.ORCID http://orcid.org/0000-0001-8567-9048

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGDM increases maternal and fetal complication risks. Fat distribution may predict risk better than total adiposity. While BMI is common, indices like BAI, ABSI, and adiposity percentage may add predictive value. This study compares these indices for GDM prediction and tests whether BMI remains the strongest predictor.

aimTo compare body fat indices in predicting gestational diabetes mellitus (GDM). MATERIALS AND

methodsThis prospective study was conducted at a tertiary hospital between March 2024 and November 2024. Pregnant patients presenting during the first trimester were included. Clinical and demographic data, waist and hip circumferences, height, weight, high-density lipoprotein, and triglyceride levels were recorded for each participant. Body mass index (BMI), body adiposity index (BAI), a-type body shape index (ABSI), and adiposity percentage were calculated. Between the 24th and 28th gestational weeks, a 75-gram oral glucose tolerance test was administered. Based on the results, the patients were grouped as GDM-positive or GDM-negative.

resultsClinical and demographic characteristics, as well as height measurements, were similar between the two groups. However, there were statistically significant differences in relation to weight, hip circumference, waist circumference, BMI, BAI, ABSI, and adiposity percentage (p < 0.005). The ROC analysis revealed that the optimal cut-off value for BMI in predicting GDM was 25.5, with 78% sensitivity and 60% specificity. For BAI, the optimal cut-off value was 30.45, with 72% sensitivity and 64% specificity. The optimal cut-off value for ABSI was 0.069 with61% sensitivity and 48% specificity. Adiposity percentage had an optimal cut-off value of 14.47, with 72% sensitivity and 74% specificity.

conclusionBMI, BAI, ABSI, and adiposity percentage are effective formulas for predicting GDM. Among these, BMI remains the most effective predictor.

Indexed as

AdiposityBody Mass IndexDiabetes, GestationalAdultFemaleGlucose Tolerance TestHumansPredictive Value of TestsPregnancyProspective StudiesABSIBAIBMIGestational Diabetes Mellitus

Identifiers

PMID41776484
PMCPMC12967719

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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.