Waist height ratio predicts chronic kidney disease: a systematic review and meta-analysis, 1998–2019
Abstract 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 ra...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Ling Liu [verfasserIn] Yanqiu Wang [verfasserIn] Wanjun Zhang [verfasserIn] Weiwei Chang [verfasserIn] Yuelong Jin [verfasserIn] Yingshui Yao [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2019 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
In: Archives of Public Health - BMC, 2013, 77(2019), 1, Seite 9 |
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| Übergeordnetes Werk: |
volume:77 ; year:2019 ; number:1 ; pages:9 |
| Links: |
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| DOI / URN: |
10.1186/s13690-019-0379-4 |
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| Katalog-ID: |
DOAJ013498118 |
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| 520 | |a Abstract 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. | ||
| 650 | 4 | |a Chronic kidney disease | |
| 650 | 4 | |a Obesity | |
| 650 | 4 | |a Physical measurement index | |
| 650 | 4 | |a Waist-to-height ratio | |
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| 700 | 0 | |a Yuelong Jin |e verfasserin |4 aut | |
| 700 | 0 | |a Yingshui Yao |e verfasserin |4 aut | |
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10.1186/s13690-019-0379-4 doi (DE-627)DOAJ013498118 (DE-599)DOAJfb6fc79649af44668540e0b828e44394 DE-627 ger DE-627 rakwb eng RA1-1270 Ling Liu verfasserin aut Waist height ratio predicts chronic kidney disease: a systematic review and meta-analysis, 1998–2019 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract 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. Chronic kidney disease Obesity Physical measurement index Waist-to-height ratio Public aspects of medicine Yanqiu Wang verfasserin aut Wanjun Zhang verfasserin aut Weiwei Chang verfasserin aut Yuelong Jin verfasserin aut Yingshui Yao verfasserin aut In Archives of Public Health BMC, 2013 77(2019), 1, Seite 9 (DE-627)378128086 (DE-600)2133388-9 20493258 nnns volume:77 year:2019 number:1 pages:9 https://doi.org/10.1186/s13690-019-0379-4 kostenfrei https://doaj.org/article/fb6fc79649af44668540e0b828e44394 kostenfrei https://doi.org/10.1186/s13690-019-0379-4 kostenfrei https://doaj.org/toc/2049-3258 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4367 GBV_ILN_4700 AR 77 2019 1 9 |
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10.1186/s13690-019-0379-4 doi (DE-627)DOAJ013498118 (DE-599)DOAJfb6fc79649af44668540e0b828e44394 DE-627 ger DE-627 rakwb eng RA1-1270 Ling Liu verfasserin aut Waist height ratio predicts chronic kidney disease: a systematic review and meta-analysis, 1998–2019 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract 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. Chronic kidney disease Obesity Physical measurement index Waist-to-height ratio Public aspects of medicine Yanqiu Wang verfasserin aut Wanjun Zhang verfasserin aut Weiwei Chang verfasserin aut Yuelong Jin verfasserin aut Yingshui Yao verfasserin aut In Archives of Public Health BMC, 2013 77(2019), 1, Seite 9 (DE-627)378128086 (DE-600)2133388-9 20493258 nnns volume:77 year:2019 number:1 pages:9 https://doi.org/10.1186/s13690-019-0379-4 kostenfrei https://doaj.org/article/fb6fc79649af44668540e0b828e44394 kostenfrei https://doi.org/10.1186/s13690-019-0379-4 kostenfrei https://doaj.org/toc/2049-3258 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4367 GBV_ILN_4700 AR 77 2019 1 9 |
| allfields_unstemmed |
10.1186/s13690-019-0379-4 doi (DE-627)DOAJ013498118 (DE-599)DOAJfb6fc79649af44668540e0b828e44394 DE-627 ger DE-627 rakwb eng RA1-1270 Ling Liu verfasserin aut Waist height ratio predicts chronic kidney disease: a systematic review and meta-analysis, 1998–2019 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract 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. Chronic kidney disease Obesity Physical measurement index Waist-to-height ratio Public aspects of medicine Yanqiu Wang verfasserin aut Wanjun Zhang verfasserin aut Weiwei Chang verfasserin aut Yuelong Jin verfasserin aut Yingshui Yao verfasserin aut In Archives of Public Health BMC, 2013 77(2019), 1, Seite 9 (DE-627)378128086 (DE-600)2133388-9 20493258 nnns volume:77 year:2019 number:1 pages:9 https://doi.org/10.1186/s13690-019-0379-4 kostenfrei https://doaj.org/article/fb6fc79649af44668540e0b828e44394 kostenfrei https://doi.org/10.1186/s13690-019-0379-4 kostenfrei https://doaj.org/toc/2049-3258 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4367 GBV_ILN_4700 AR 77 2019 1 9 |
| allfieldsGer |
10.1186/s13690-019-0379-4 doi (DE-627)DOAJ013498118 (DE-599)DOAJfb6fc79649af44668540e0b828e44394 DE-627 ger DE-627 rakwb eng RA1-1270 Ling Liu verfasserin aut Waist height ratio predicts chronic kidney disease: a systematic review and meta-analysis, 1998–2019 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract 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. Chronic kidney disease Obesity Physical measurement index Waist-to-height ratio Public aspects of medicine Yanqiu Wang verfasserin aut Wanjun Zhang verfasserin aut Weiwei Chang verfasserin aut Yuelong Jin verfasserin aut Yingshui Yao verfasserin aut In Archives of Public Health BMC, 2013 77(2019), 1, Seite 9 (DE-627)378128086 (DE-600)2133388-9 20493258 nnns volume:77 year:2019 number:1 pages:9 https://doi.org/10.1186/s13690-019-0379-4 kostenfrei https://doaj.org/article/fb6fc79649af44668540e0b828e44394 kostenfrei https://doi.org/10.1186/s13690-019-0379-4 kostenfrei https://doaj.org/toc/2049-3258 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4367 GBV_ILN_4700 AR 77 2019 1 9 |
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10.1186/s13690-019-0379-4 doi (DE-627)DOAJ013498118 (DE-599)DOAJfb6fc79649af44668540e0b828e44394 DE-627 ger DE-627 rakwb eng RA1-1270 Ling Liu verfasserin aut Waist height ratio predicts chronic kidney disease: a systematic review and meta-analysis, 1998–2019 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract 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. Chronic kidney disease Obesity Physical measurement index Waist-to-height ratio Public aspects of medicine Yanqiu Wang verfasserin aut Wanjun Zhang verfasserin aut Weiwei Chang verfasserin aut Yuelong Jin verfasserin aut Yingshui Yao verfasserin aut In Archives of Public Health BMC, 2013 77(2019), 1, Seite 9 (DE-627)378128086 (DE-600)2133388-9 20493258 nnns volume:77 year:2019 number:1 pages:9 https://doi.org/10.1186/s13690-019-0379-4 kostenfrei https://doaj.org/article/fb6fc79649af44668540e0b828e44394 kostenfrei https://doi.org/10.1186/s13690-019-0379-4 kostenfrei https://doaj.org/toc/2049-3258 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4367 GBV_ILN_4700 AR 77 2019 1 9 |
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Waist height ratio predicts chronic kidney disease: a systematic review and meta-analysis, 1998–2019 |
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Abstract 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. |
| abstractGer |
Abstract 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. |
| abstract_unstemmed |
Abstract 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. |
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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. 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