Prevalence and risk factors of chronic kidney disease and diabetic kidney disease in Chinese rural residents: a cross-sectional survey

Sci Rep. 2019 Jul 18;9(1):10408. doi: 10.1038/s41598-019-46857-7.


We conducted a cross-sectional survey including 23869 participants and aimed to measure the prevalences of and risk factors for chronic kidney disease (CKD) and diabetic kidney disease (DKD) in a Chinese rural population. CKD and DKD status was defined according to the combination of estimated glomerular filtration rate (eGFR) and presence of albuminuria Participant completed a questionnaire involving life-style and relevant medical history, and the blood and urinary specimen were taken. The age- and gender- adjusted prevalences of CKD and DKD were calculated and risk factors associated with the presence of CKD and DKD were analyzed by logistic regression. The overall prevalence of CKD was 16.4% (15.9-16.8%) and of DKD was 2.9% (2.7-3.1%). In participants with diabetes, the overall prevalence of CKD was 35.5% (95% CI = 33.7-37.3%). Factors independently associated with renal damage were age, gender, education, personal income, alcohol consumption, overweight, obesity, diabetes, hypertension and dyslipidemia. Our study shows current prevalences of CKD and DKD in Chinese rural residents. Further researches could identify potential factors explaining the observed differences and implement the interventions to relieve the high burden of CKD and DKD in rural population.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Asian People
  • Cross-Sectional Studies
  • Diabetes Mellitus / physiopathology
  • Diabetic Nephropathies / etiology*
  • Female
  • Glomerular Filtration Rate / physiology
  • Humans
  • Hypertension / complications
  • Kidney / physiopathology
  • Male
  • Middle Aged
  • Obesity / complications
  • Prevalence
  • Renal Insufficiency, Chronic / etiology*
  • Risk Factors
  • Rural Population / statistics & numerical data
  • Urban Population / statistics & numerical data