Estimated glomerular filtration rate trajectories in south Asians: Findings from the cardiometabolic risk reduction in south Asia study

• Type of Material: Article
• Authors: Ram Jagannathan, Emory University; Shuchi Anand, Centers for Chronic Disease Control, India; Julien Hogan, Emory University; Siddhartha Mandal, Centers for Chronic Disease Control, India; Dimple Kondal, Emory University; Ruby Gupta, Centers for Chronic Disease Control, India; Ruby Mohan Anjana, Emory University; Shivani Patel, Emory University; Mohan Deepa, Emory University; Mohammed Ali, Emory University; Viswanathan Mohan, Emory University; Nikhil Tandon, All India Institute of Medical Sciences, New Delhi; K.M. Venkat Narayan, Emory University; Dorairaj Prabhakaran, Emory University
• Language: English
• Date: 2022-11-01
• Publisher: Elsevier Ltd
• Publication Version: Final Published Version
• Copyright Statement: © 2022 The Author(s)
• License: Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International
• Final Published Version (URL): http://dx.doi.org/10.1016/j.lansea.2022.100062
• Title of Journal or Parent Work: The Lancet Regional Health - Southeast Asia
• Volume: 6
• Start Page: 100062
• End Page: 100062
• Keywords: Latent class trajectory modeling; South Asians; Albuminuria; Personalized medicine; eGFR trajectories
• Research Categories: Health Sciences, Medicine and Surgery

Abstract

Background: Few longitudinal data characterize kidney function decline among South Asians, one of the world's largest population groups. We aimed to identify estimated glomerular filtration rate (eGFR) trajectories in a population-based cohort from India and assess predictors of rapid kidney function decline. Methods: We used 6-year longitudinal data from participants of a population-representative study from Delhi and Chennai, India who had at least two serum creatinine measures and baseline CKD-EPI eGFR> 60 ml/min/1.73m2 (n=7779). We used latent class trajectory modeling to identify patterns of kidney function trajectory (CKD-EPI eGFR) over time. In models accounting for age, sex, education, and city, we tested the association between 15 hypothesized risk factors and rapid kidney function decline. Findings: Baseline mean eGFR was 108 (SD 16); median eGFR was 110 [IQR: 99-119] ml/min/1.73m2. Latent class trajectory modeling and functional characterization identified three distinct patterns of eGFR: class-1 (no decline; 58%) annual eGFR change 0.2 [0.1, 0.3]; class-2 (slow decline; 40%) annual eGFR change −0.2 [−0.4, −0.1], and class-3 (rapid decline; 2%) annual eGFR change −2.7 [−3.4, −2.0] ml/min/1.73m2. Albuminuria (>30 mg/g) was associated with rapid eGFR decline (OR for class-3 vs class-1: 5.1 [95% CI: 3.2; 7.9]; class-3 vs. class-2: 4.3 [95% CI:2.7; 6.6]). Other risk factors including self-reported diabetes, cardiovascular disease, peripheral arterial disease, and metabolic biomarkers such as HbA1c and systolic blood pressure were associated with rapid eGFR decline phenotype but potential ‘non-traditional’ risk factors such as manual labor or household water sources were not. Interpretation: Although mean and median eGFRs in our population-based cohort were higher than those reported in European cohorts, we found that a sizeable number of adults residing in urban India are experiencing rapid kidney function decline. Early and aggressive risk modification among persons with albuminuria could improve kidney health among South Asians. Funding: The CARRS study has been funded with federal funds from the National Heart, Lung, and Blood Institute, National Institutes of Health, under Contract No. HHSN2682009900026C and P01HL154996. Dr. Anand was supported by NIDDK K23DK101826 and R01DK127138.