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Waist height ratio predicts chronic kidney disease: a systematic review and meta-analysis, 1998–2019
BACKGROUND: The incidence of chronic kidney disease (CKD) increases each year, and obesity is an important risk factor for CKD. The main anthropometric indicators currently reflecting obesity are body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR) and waist-to-height ratio (WHt...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6918668/ https://www.ncbi.nlm.nih.gov/pubmed/31867106 http://dx.doi.org/10.1186/s13690-019-0379-4 |
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author | Liu, Ling Wang, Yanqiu Zhang, Wanjun Chang, Weiwei Jin, Yuelong Yao, Yingshui |
author_facet | Liu, Ling Wang, Yanqiu Zhang, Wanjun Chang, Weiwei Jin, Yuelong Yao, Yingshui |
author_sort | Liu, Ling |
collection | PubMed |
description | BACKGROUND: The incidence of chronic kidney disease (CKD) increases each year, and obesity is an important risk factor for CKD. The main anthropometric indicators currently reflecting obesity are body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR) and waist-to-height ratio (WHtR), but the rationality and merits of various indicators vary. This article aims to find whether the WHtR is a more suitable physical measurement that can predict CKD. METHODS: Pubmed, embase, the cochrane library, and web of science were systematically searched for articles published between 1998 and 2019 screening CKD through physical indicators. Two reviewers independently screened the literature according to the inclusion and exclusion criteria, extracted the data, and evaluated the quality of the methodology included in the study. Meta-analysis used the Stata 12.0 software. RESULTS: Nine studies were included, with a total of 202,283 subjects. Meta-analysis showed that according to the analysis of different genders in 6 studies, regardless of sex, WHtR was the area with the largest area under the curve (AUC). Except WHtR and visceral fat index (VFI) in women which showed no statistical difference, WHtR and other indicators were statistically different. In three studies without gender-based stratification, the area under the curve AUC for WHtR remained the largest, but only the difference between WHtR and BMI was statistically significant. When the Chinese population was considered as a subgroup, the area under the curve AUC for WHtR was the largest. Except for WHtR and VFI which showed no statistical difference in women, there was a statistically significant difference between WHtR and other indicators in men and women. CONCLUSION: WHtR could be better prediction for CKD relative to other physical measurements. It also requires higher-quality prospective studies to verify the clinical application of WHtR. |
format | Online Article Text |
id | pubmed-6918668 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-69186682019-12-20 Waist height ratio predicts chronic kidney disease: a systematic review and meta-analysis, 1998–2019 Liu, Ling Wang, Yanqiu Zhang, Wanjun Chang, Weiwei Jin, Yuelong Yao, Yingshui Arch Public Health Research BACKGROUND: The incidence of chronic kidney disease (CKD) increases each year, and obesity is an important risk factor for CKD. The main anthropometric indicators currently reflecting obesity are body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR) and waist-to-height ratio (WHtR), but the rationality and merits of various indicators vary. This article aims to find whether the WHtR is a more suitable physical measurement that can predict CKD. METHODS: Pubmed, embase, the cochrane library, and web of science were systematically searched for articles published between 1998 and 2019 screening CKD through physical indicators. Two reviewers independently screened the literature according to the inclusion and exclusion criteria, extracted the data, and evaluated the quality of the methodology included in the study. Meta-analysis used the Stata 12.0 software. RESULTS: Nine studies were included, with a total of 202,283 subjects. Meta-analysis showed that according to the analysis of different genders in 6 studies, regardless of sex, WHtR was the area with the largest area under the curve (AUC). Except WHtR and visceral fat index (VFI) in women which showed no statistical difference, WHtR and other indicators were statistically different. In three studies without gender-based stratification, the area under the curve AUC for WHtR remained the largest, but only the difference between WHtR and BMI was statistically significant. When the Chinese population was considered as a subgroup, the area under the curve AUC for WHtR was the largest. Except for WHtR and VFI which showed no statistical difference in women, there was a statistically significant difference between WHtR and other indicators in men and women. CONCLUSION: WHtR could be better prediction for CKD relative to other physical measurements. It also requires higher-quality prospective studies to verify the clinical application of WHtR. BioMed Central 2019-12-18 /pmc/articles/PMC6918668/ /pubmed/31867106 http://dx.doi.org/10.1186/s13690-019-0379-4 Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Liu, Ling Wang, Yanqiu Zhang, Wanjun Chang, Weiwei Jin, Yuelong Yao, Yingshui Waist height ratio predicts chronic kidney disease: a systematic review and meta-analysis, 1998–2019 |
title | Waist height ratio predicts chronic kidney disease: a systematic review and meta-analysis, 1998–2019 |
title_full | Waist height ratio predicts chronic kidney disease: a systematic review and meta-analysis, 1998–2019 |
title_fullStr | Waist height ratio predicts chronic kidney disease: a systematic review and meta-analysis, 1998–2019 |
title_full_unstemmed | Waist height ratio predicts chronic kidney disease: a systematic review and meta-analysis, 1998–2019 |
title_short | Waist height ratio predicts chronic kidney disease: a systematic review and meta-analysis, 1998–2019 |
title_sort | waist height ratio predicts chronic kidney disease: a systematic review and meta-analysis, 1998–2019 |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6918668/ https://www.ncbi.nlm.nih.gov/pubmed/31867106 http://dx.doi.org/10.1186/s13690-019-0379-4 |
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