Prevalence of chronic kidney disease in two major Indian cities and projections for associated cardiovascular disease

Abstract

India is experiencing an alarming rise in the burden of noncommunicable diseases, but data on the incidence of chronic kidney disease (CKD) are sparse. Using the Center for Cardiometabolic Risk Reduction in South Asia surveillance study (a population-based survey of Delhi and Chennai, India) we estimated overall, and age-, sex-, city-, and diabetes-specific prevalence of CKD, and defined the distribution of the study population by the Kidney Disease Improving Global Outcomes (KDIGO) classification scheme. The likelihood of cardiovascular events in participants with and without CKD was estimated by the Framingham and Interheart Modifiable Risk Scores. Of the 12,271 participants, 80% had complete data on serum creatinine and albuminuria. The prevalence of CKD and albuminuria, age standardized to the World Bank 2010 world population, was 8.7% (95% confidence interval: 7.9-9.4%) and 7.1% (6.4-7.7%), respectively. Nearly 80% of patients with CKD had an abnormally high hemoglobin A1c (5.7 and above). Based on KDIGO guidelines, 6.0, 1.0, and 0.5% of study participants are at moderate, high, or very high risk for experiencing CKD-associated adverse outcomes. The cardiovascular risk scores placed a greater proportion of patients with CKD in the high-risk categories for experiencing cardiovascular events when compared with participants without CKD. Thus, 1 in 12 individuals living in two of India's largest cities have evidence of CKD, with features that put them at high risk for adverse outcomes.

Figure 1. CKD prevalence according to age categories and stage of CKD

CKD prevalence in the CARRS study according to age categories and stage. a-c represent Chennai; d-f represent Delhi. Error bars represent 95% confidence intervals. Stage 1 or 2 CKD identifies patients with albuminuria (≥ 30 mg/g) and eGFR ≥ 60 ml/min/1.73m²; Stage 3 to 5 CKD identifies patients with eGFR < 60 ml/min/1.73m². Abbreviations: CARRS-Center for Cardiometabolic Risk Reduction in South Asia; CKD-Chronic kidney disease; eGFR-estimated glomerular filtration rate.

Figure 1. CKD prevalence according to age categories and stage of CKD

CKD prevalence in the CARRS study according to age categories and stage. a-c represent Chennai; d-f represent Delhi. Error bars represent 95% confidence intervals. Stage 1 or 2 CKD identifies patients with albuminuria (≥ 30 mg/g) and eGFR ≥ 60 ml/min/1.73m²; Stage 3 to 5 CKD identifies patients with eGFR < 60 ml/min/1.73m². Abbreviations: CARRS-Center for Cardiometabolic Risk Reduction in South Asia; CKD-Chronic kidney disease; eGFR-estimated glomerular filtration rate.

Figure 1. CKD prevalence according to age categories and stage of CKD

CKD prevalence in the CARRS study according to age categories and stage. a-c represent Chennai; d-f represent Delhi. Error bars represent 95% confidence intervals. Stage 1 or 2 CKD identifies patients with albuminuria (≥ 30 mg/g) and eGFR ≥ 60 ml/min/1.73m²; Stage 3 to 5 CKD identifies patients with eGFR < 60 ml/min/1.73m². Abbreviations: CARRS-Center for Cardiometabolic Risk Reduction in South Asia; CKD-Chronic kidney disease; eGFR-estimated glomerular filtration rate.

Figure 1. CKD prevalence according to age categories and stage of CKD

CKD prevalence in the CARRS study according to age categories and stage. a-c represent Chennai; d-f represent Delhi. Error bars represent 95% confidence intervals. Stage 1 or 2 CKD identifies patients with albuminuria (≥ 30 mg/g) and eGFR ≥ 60 ml/min/1.73m²; Stage 3 to 5 CKD identifies patients with eGFR < 60 ml/min/1.73m². Abbreviations: CARRS-Center for Cardiometabolic Risk Reduction in South Asia; CKD-Chronic kidney disease; eGFR-estimated glomerular filtration rate.

Figure 2

Confluence of abnormally high A1c, hypertension, and CKD in the CARRS study. Eighty-six percent of participants with CKD had either abnormal A1c (≥ 5.7) and/or hypertension. Abbreviations: CKD-Chronic kidney disease; CARRS-Center for Cardiometabolic Risk Reduction in South Asia.

Figure 3

Distribution of Framingham and Interheart Modifiable Risk Scores according to CKD status. Using the FRS, 30.8% (95% CI: 25.9 to 35.8%) of participants with CKD were placed in the high-risk category (>20% likelihood) for experiencing a cardiovascular event in the next 10 years, with a prevalence difference of 21.8% (95% CI: 17.3 to 26.3%) from the participants without CKD. Using the Interheart Modifiable Risk Score, 49.2% (95% CI: 44.5 to 53.8%) of participants were in the high-risk category (> 5 fold increase in odds of myocardial infarction over the next 3 years), with a prevalence difference of 26.3% (95% CI: 21.9 to 30.6%) from participants without CKD.

Figure 3

Distribution of Framingham and Interheart Modifiable Risk Scores according to CKD status. Using the FRS, 30.8% (95% CI: 25.9 to 35.8%) of participants with CKD were placed in the high-risk category (>20% likelihood) for experiencing a cardiovascular event in the next 10 years, with a prevalence difference of 21.8% (95% CI: 17.3 to 26.3%) from the participants without CKD. Using the Interheart Modifiable Risk Score, 49.2% (95% CI: 44.5 to 53.8%) of participants were in the high-risk category (> 5 fold increase in odds of myocardial infarction over the next 3 years), with a prevalence difference of 26.3% (95% CI: 21.9 to 30.6%) from participants without CKD.