Evidence map›Paper›PMID 36757992›Full record

ArticlePloS one2023

Association of intraabdominal fat with the risk of incident chronic kidney disease according to body mass index among Korean adults.

Jeonghwan Lee, Seran Min, Seung-Won Oh, Sohee Oh, Yoon-Hye Lee, Hyuktae Kwon, Cheol Min Lee, Ho-Chun Choi, Nam Ju Heo

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
2.4field-weighted citation impact, top 11% 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

7 citing papers in PubMed, 11 citations in OpenAlex.

  1. Article
  2. Article
  3. Cardio-kidney-metabolic (CKM) framework: A nephrologist's perspective.Archives of endocrinology and metabolism · 2025
    Review
  4. Review
  5. Article
  6. Article
  7. 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 2 institutions in 1 country.

Jeonghwan LeeDepartment of Internal Medicine, Boramae Medical Center, Seoul National University Hospital, Seoul, South Korea.ORCID 0000-0003-3199-635X
Seran MinDepartment of Family Medicine, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, South Korea.
Seung-Won OhDepartment of Family Medicine, Healthcare System Gangnam Center of Seoul National University Hospital, Seoul, South Korea.ORCID 0000-0003-3800-0754
Sohee OhMedical Research Collaborating Center, Seoul National University Boramae Medical Center, Seoul, South Korea.ORCID 0000-0002-3010-448X
Yoon-Hye LeeDepartment of Family Medicine, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, South Korea.
Hyuktae KwonDepartment of Family Medicine, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, South Korea.ORCID 0000-0002-0312-3650
Cheol Min LeeDepartment of Family Medicine, Healthcare System Gangnam Center of Seoul National University Hospital, Seoul, South Korea.
Ho-Chun ChoiDepartment of Family Medicine, Healthcare System Gangnam Center of Seoul National University Hospital, Seoul, South Korea.
Nam Ju HeoDepartment of Internal Medicine, Healthcare System Gangnam Center, Seoul National University Hospital, Seoul, South Korea.ORCID 0000-0003-3721-4830
Seoul National University Hospital · KRSeoul National University · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe association between abdominal visceral adipose tissue and the risk of incident chronic kidney disease according to body mass index in the Asian population, remains unclear. We evaluated the impact of abdominal adiposity stratified by body mass index on the risk of incident chronic kidney disease.

methodsA cohort study included 11,050 adult participants who underwent health check-ups and re-evaluated the follow-up medical examination at a single university-affiliated healthcare center. Cross-sectional abdominal adipose tissue areas were measured using computed tomography. The primary outcome was progression to chronic kidney disease (estimated glomerular filtration rate <60 ml/min/1.73m2). The highest quartile of visceral adipose tissue was used for the cut-off of central obesity.

resultsDuring the mean of 5.6 follow-up years, 104 incident chronic kidney disease cases were identified. The risk for chronic kidney disease incidence was significantly increased in the 3rd and 4th quartile ranges of visceral adipose tissue [hazard ratio (95% confidence interval)]: 4.59 (1.48-14.30) and 7.50 (2.33-24.20), respectively. In the analysis stratified by body mass index, the chronic kidney disease incidence risk was increased in the highest quartile range of visceral adipose tissue in the normal weight group: 7.06 (1.35-37.04). However, there was no significant relationship between visceral adipose tissue and chronic kidney disease in the obese group. Compared to the subjects with normal weight and absent central obesity, the hazard ratio for chronic kidney disease incidence was 2.32 (1.26-4.27) among subjects with normal weight and central obesity and 1.81 (1.03-3.15) among subjects with obesity and central obesity.

conclusionVisceral adipose tissue was a significant risk factor for subsequent chronic kidney disease progression, and the association was identified only in the normal weight group. Normal-weight central obesity was associated with excess risk of chronic kidney disease, similar to the risk in the group with obesity and central obesity.

Indexed as

Intra-Abdominal FatRenal Insufficiency, ChronicAdultBody Mass IndexCohort StudiesCross-Sectional StudiesHumansObesityObesity, AbdominalRepublic of KoreaRisk Factors

Identifiers

PMID36757992
PMCPMC9910748
OpenAlexW4319656796

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.