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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 studyResearch areaResearch periodResearch methodsData SourcesSample size (n)AgeNumber of CKD patients (n)Quality Evaluation
malefemalemalefemalemalefemale
Dong 2018 [11]China2012–2015cross-sectional surveyRandomly sampled population survey data across 31 provinces and cities in the Middle East and West China13,41016,10656.48 ± 13.1356.48 ± 13.136838958
Dai 2016 [12]China2012–2013cross-sectional surveyMulti-stage stratified randomized cluster sampling data from representative populations in Liaoning Province, China51686024≥35≥35851528
Jaroszynski 2016 [13]Britaincross-sectional surveyPopulation survey data for some rural areas in the United Kingdom73071.4 ± 4.98898
Odagiri 2014 [14]Japan2008–2011cohort studyJapanese company employees’ medical data3686115518–6718–67300847
Liu 2016 [15]China2013–2014cross-sectional surveyHospital health checkup data in Hunan Province15,59311,06218–8018–8014963389
He 2016 [16]China2008–2009cross-sectional surveyMulti-stage cluster sampling health check data for Chinese cities78,14245,48745.1 ± 14.244.3 ± 13.5462915168
Bulum 2016 [17]Croatiacross-sectional surveyThe annual physical examination data of T2DM consecutive male and female patients656031–76369
Lin 2007 [18]China2003–2005cross-sectional surveyTaizhou City University of Traditional Chinese Medicine Affiliated Hospital Crowd Health Examination Data2613199828–832219
Chou 2008 [19]China2003–2005cross-sectional surveyPopulation health check data at Affiliated Hospital of China Medical University53744766.7 ± 5.31618