Evidence map›Paper›PMID 36824322›Full record

ArticleDiabetes, metabolic syndrome and obesity : targets and therapy2023

Visceral Adiposity Index and Lipid Accumulation Product as Effective Markers of Different Obesity Phenotypes in Korean Adults: A Cross-Sectional Analysis.

Sung Ryul Yu, Kyung-A Shin

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In one paragraph

Article in Diabetes, metabolic syndrome and obesity : targets and therapy, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

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0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
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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

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3 · Its place in the literature

Who cites it

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

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  4. Associations Between Dietary Diversity Score and Adiposity Indexes in Obese AdolescentsJournal of clinical research in pediatric endocrinology · 2026
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4 · The record

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5 · Who and what money

Authors and funding

2 authors.

Sung Ryul YuDepartment of Clinical Laboratory Science, Semyung University, Jaecheon, Republic of Korea.ORCID 0000-0003-4720-3748
Kyung-A ShinDepartment of Clinical Laboratory Science, Shinsung University, Dangjin, Republic of Korea.ORCID 0000-0001-5266-5627

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: The visceral adiposity index (VAI) and lipid accumulation product (LAP) are useful for assessing visceral obesity. However, these indices were developed for Caucasians, and it is necessary to confirm whether the VAI and LAP are appropriate indicators for identifying obesity phenotypes in Asians. This study investigated whether the VAI and LAP are effective indicators for diagnosing four obesity phenotypes in South Korean adults. Patients and Methods: This cross-sectional study enrolled 23,310 adult participants (age ≥20 years) who had undergone a health checkup at a general hospital in Gyeonggi-do, South Korea from January 2017 to December 2020. VAI and LAP were calculated based on the presented mathematical model according to sex. According to the metabolic health status and presence or absence of obesity, the obesity phenotypes were classified into 4 groups: metabolically healthy non-obese (N=14,240, 61.1%), metabolically unhealthy non-obese (N=477, 2.0%), metabolically healthy obese (MHO; N=6796, 29.2%), and metabolically unhealthy obesity (MUO; N=1797, 7.7%). Results: The receiver operating characteristics curve analysis showed VAI best predicted MUO among the four obesity phenotypes, whereas the LAP showed excellent discriminating ability for the MUO group (area under the curve 0.877, 0.849, and 0.921 and 0.923, 0.907, and 0.954 for all participants, men, and women, respectively). The optimal VAI cutoff values for identifying the MUO group were 1.83 in men and 1.58 in women, and the optimal cutoff values for the LAP were 41.45 in men and 23.83 in women, with a higher value for men. After adjusting for potential confounding factors, the VAI and LAP were associated with an increased risk in the MHO and MUO groups among the obesity phenotypes in both sexes. Conclusion: In South Korean adults, the VAI and LAP are closely related to the MUO phenotype in both sexes and are effective indices for predicting the MUO phenotype.

Indexed as

lipid accumulation productmetabolic syndromeobesity phenotypevisceral adiposity index

Identifiers

PMID36824322
PMCPMC9942502

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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.