Application of machine learning techniques to understand ethnic differences and risk factors for incident chronic kidney disease in Asians

Abstract

Introduction Chronic kidney disease (CKD) is increasing in Asia, but there are sparse data on incident CKD among different ethnic groups. We aimed to describe the incidence and risk factors associated with CKD in the three major ethnic groups in Asia: Chinese, Malays and Indians. Research design and methods Prospective cohort study of 5580 general population participants age 40-80 years (2234 Chinese, 1474 Malays and 1872 Indians) who completed both baseline and 6-year follow-up visits. Incident CKD was defined as an estimated glomerular filtration rate (eGFR) <60 mL/min/1.73 m 2 in those free of CKD at baseline. Results The 6-year incidence of CKD was highest among Malays (10.0%), followed by Chinese (6.1%) and Indians (5.8%). Logistic regression showed that older age, diabetes, higher systolic blood pressure and lower eGFR were independently associated with incident CKD in all three ethnic groups, while hypertension and cardiovascular disease were independently associated with incident CKD only in Malays. The same factors were identified by machine learning approaches, gradient boosted machine and random forest to be the most important for incident CKD. Adjustment for clinical and socioeconomic factors reduced the excess incidence in Malays by 60% compared with Chinese but only 13% compared with Indians. Conclusion Incidence of CKD is high among the main Asian ethnic groups in Singapore, ranging between 6% and 10% over 6 years; differences were partially explained by clinical and socioeconomic factors.