Large Cohort Study
Prevalence of chronic kidney disease and its association with lifestyle factors in adults from 10 regions of China
Wang Xue, Shi Kexiang, Yu Canqing, Lyu Jun, Guo Yu, Pei Pei, Xia Qingmei, Du Huaidong, Chen Junshi, Chen Zhengming, Li Liming, for the China Kadoorie Biobank Collaborative Group
Published 2023-03-10
Cite as Chin J Epidemiol, 2023, 44(3): 386-392. DOI: 10.3760/cma.j.cn112338-20220801-00680
Abstract
ObjectiveTo investigate the distribution of chronic kidney disease (CKD) in participants from the China Kadoorie Biobank (CKB) study and evaluate the association between lifestyle risk factors and CKD.
MethodsBased on the baseline survey data and follow-up data (as of December 31, 2018) of the CKB study, the differences in CKD cases' area and population distributions were described. Cox proportional hazards regression model was used to estimate the association between lifestyle risk factors and the risk of CKD.
ResultsA total of 505 147 participants, 4 920 cases of CKD were recorded in 11.26 year follow up with a incidence rate of 83.43/100 000 person-years. Glomerulonephropathy was the most common type. The incidence of CKD was higher in the urban area, men, and the elderly aged 60 years and above (87.83/100 000 person-years, 86.37/100 000 person-years, and 132.06/100 000 person-years). Current male smokers had an increased risk for CKD compared with non-smokers or occasional smokers (HR=1.18, 95%CI: 1.05-1.31). The non-obese population was used as a control group, both general obesity determined by BMI (HR=1.19, 95%CI: 1.10-1.29) and central obesity determined by waist circumference (HR=1.27, 95%CI: 1.19-1.35) were associated with higher risk for CKD.
ConclusionThe risks for CKD varied with area and population in the CKB cohort study, and the risk was influenced by multiple lifestyle factors.
Key words:
Chronic kidney disease; Disease distribution; Lifestyle factor; Prospective cohort study
Contributor Information
Wang Xue
Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191,China
Shi Kexiang
Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191,China
Yu Canqing
Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191,China
Peking University Center for Public Health and Epidemic Preparedness &
Response, Beijing 100191,China
Lyu Jun
Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191,China
Peking University Center for Public Health and Epidemic Preparedness &
Response, Beijing 100191,China
Guo Yu
Fuwai Hospital, Chinese Academy of Medical Sciences, National Center for Cardiovascular Diseases, Beijing 100037, China
Pei Pei
Chinese Academy of Medical Sciences, Beijing 100730, China
Xia Qingmei
Chinese Academy of Medical Sciences, Beijing 100730, China
Du Huaidong
Nuffield Department of Population Health, Center for Clinical and Epidemiological Studies, University of Oxford, Oxford OX3 7LF, UK
Chen Junshi
China National Center for Food Safety Risk Assessment, Beijing 100022, China
Chen Zhengming
Nuffield Department of Population Health, Center for Clinical and Epidemiological Studies, University of Oxford, Oxford OX3 7LF, UK
Li Liming
Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191,China
Peking University Center for Public Health and Epidemic Preparedness &
Response, Beijing 100191,China
for the China Kadoorie Biobank Collaborative Group
