Evidence map›Paper›PMID 38834991›Full record

ArticleBMC endocrine disorders2024

Assessment of the appropriate cutoff points for anthropometric indices and their relationship with cardio-metabolic indices to predict the risk of metabolic associated fatty liver disease.

Seyed Ahmad Hosseini, Meysam Alipour, Sara Sarvandian, Neda Haghighat, Hadi Bazyar, Ladan Aghakhani

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Article in BMC endocrine disorders, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed, 1 pooled it
–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

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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

18 citing papers in PubMed, 1 synthesis or guideline 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

6 authors.

Seyed Ahmad HosseiniNutrition and Metabolic Disease Research CenterClinical Sciences Research Institute, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran.
Meysam AlipourDepartment of Nutrition, Shoushtar Faculty of Medical Sciences, Shoushtar, Iran.
Sara SarvandianDepartment of Nutrition, Shoushtar Faculty of Medical Sciences, Shoushtar, Iran.
Neda HaghighatLaparoscopy Research Center, Shiraz University of Medical Sciences, Shiraz, Iran.
Hadi BazyarDepartment of Public Health, Sirjan School of Medical Sciences, Sirjan, Iran.
Ladan AghakhaniLaparoscopy Research Center, Shiraz University of Medical Sciences, Shiraz, Iran. ladan.aghakhani@gmail.com.ORCID http://orcid.org/0000-0002-5666-4629

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundResearch on Metabolic Associated Fatty Liver Disease (MAFLD) is still in its early stages, with few studies available to identify and predict effective indicators of this disease. On the other hand, early diagnosis and intervention are crucial to reduce the burden of MAFLD. Therefore, the aim of this research was to investigate the effectiveness of eleven anthropometric indices and their appropriate cut-off values as a non-invasive method to predict and diagnose MAFLD in the Iranian population.

methodsIn this cross-sectional study, we analyzed baseline data from the Hoveyzeh Cohort Study, a prospective population-based study conducted in Iran that enrolled a total of 7836 subjects aged 35 to 70 years from May 2016 through August 2018.

resultsThe optimal cut-off values of anthropometric indices for predicting MAFLD risk were determined for waist circumference(WC) (102.25 cm for males and 101.45 cm for females), body mass index (BMI) (27.80 kg/m

conclusionAnthropometric indices are effective in predicting MAFLD risk among Iranian adults, with WWI, VAI, and RFM identified as the strongest predictors. The proposed cutoff values could serve as a straightforward and non-invasive methods for the early diagnosis of MAFLD.

Indexed as

AnthropometryAdiposityAdultAgedBody Mass IndexCross-Sectional StudiesFemaleFollow-Up StudiesHumansIranMaleMetabolic SyndromeMiddle AgedNon-alcoholic Fatty Liver DiseasePrognosisProspective StudiesBody mass indexCardiovascular diseasesFatty liverMetabolic diseasesNutrition assessment

Identifiers

PMID38834991
PMCPMC11151590

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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.