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Table 1 The main characteristics and quality evaluation of the included studies (by gender). A systematic review and meta-analysis on the waist height and chronic kidney disease, 1998–2019

From: Waist height ratio predicts chronic kidney disease: a systematic review and meta-analysis, 1998–2019

Inclusion study

Research area

Research period

Research methods

Data Sources

Sample size (n)

Age

Number of CKD patients (n)

Quality Evaluation

male

female

male

female

male

female

Dong 2018 [11]

China

2012–2015

cross-sectional survey

Randomly sampled population survey data across 31 provinces and cities in the Middle East and West China

13,410

16,106

56.48 ± 13.13

56.48 ± 13.13

683

895

8

Dai 2016 [12]

China

2012–2013

cross-sectional survey

Multi-stage stratified randomized cluster sampling data from representative populations in Liaoning Province, China

5168

6024

≥35

≥35

85

152

8

Jaroszynski 2016 [13]

Britain

cross-sectional survey

Population survey data for some rural areas in the United Kingdom

730

71.4 ± 4.98

89

8

Odagiri 2014 [14]

Japan

2008–2011

cohort study

Japanese company employees’ medical data

3686

1155

18–67

18–67

300

84

7

Liu 2016 [15]

China

2013–2014

cross-sectional survey

Hospital health checkup data in Hunan Province

15,593

11,062

18–80

18–80

1496

338

9

He 2016 [16]

China

2008–2009

cross-sectional survey

Multi-stage cluster sampling health check data for Chinese cities

78,142

45,487

45.1 ± 14.2

44.3 ± 13.5

4629

1516

8

Bulum 2016 [17]

Croatia

cross-sectional survey

The annual physical examination data of T2DM consecutive male and female patients

65

60

31–76

36

9

Lin 2007 [18]

China

2003–2005

cross-sectional survey

Taizhou City University of Traditional Chinese Medicine Affiliated Hospital Crowd Health Examination Data

2613

1998

28–83

221

9

Chou 2008 [19]

China

2003–2005

cross-sectional survey

Population health check data at Affiliated Hospital of China Medical University

537

447

66.7 ± 5.3

161

8