Supplementary Material for: A comprehensive report on the self-reported chronic kidney disease patients in the NHANES cross-sectional cohort from 2001-2020

Background
This study was a comprehensive review of the Centers for Disease Control and Prevention (CDC) National Health and Nutrition Examination (NHANES) databases. The primary objectives were to ascertain patterns of demographic and clinical data among chronic kidney disease (CKD) and dialysis patients.
Methods
This study examines participants from the CDC NHANES database to identify the population diagnosed with chronic kidney disease or dialysis patients from 2001-2020. The total cohort of 51,743 patients were included in each group, i.e., CKD group included 1509 patients (out of which 173 patients have received dialysis in the past 12 months), while non-CKD group included 50,234 patients. Exclusion criteria included age >85 years (n=624), pregnancy (n=1375), and history of malignancy (n=5575). Logistic regression was performed to identify conditions that were more frequently observed with CKD and those on dialysis with reported odds ratios (OR). Receiver operating characteristics (ROC) analysis was used to calculate diagnostic accuracies of different cut-offs for urinary albumin-to-creatinine ratio (UACR).
Results
The mean age of study participants (n=51,743) was 48.50±17.43 years. Age was significantly higher in CKD group but there was no difference in dialysis versus non-dialysis patients (P=0.833). There was no gender predisposition in CKD patients however, males were more likely to undergo dialysis with 13.3% vs 9.8% in females (P=0.032). Among racial differences, Non Hispanic Whites were predominantly affected by CKD (37.0%) followed by non-Hispanic Blacks (29.3%) but non-Hispanic Blacks are mostly undergoing dialysis (48.6% vs 17.3%). BMI (kg/m2) was significantly higher in CKD group (P<0.001), but lower in dialysis group (P=0.039). Among urinary complaints, history of kidney stones was prevalent in CKD patients (7.7% vs 2.6%, P<0.001). Frequent coexisting comorbidities were congestive heart failure (OR: 9.8), diabetes (OR: 5.4), Coronary artery disease (OR: 5.0), and hypertension (OR: 4.7). UACR (>30 mg/g) is able to categorize CKD patients (AUC: 0.73), at a sensitivity of 44.9% and a specificity of 88.8%.
Conclusion
Certain clinical factors were identified as highly associated with CKD, as disseminated by the NHANES database findings. These findings emphasize the need for targeted interventions to address CKD disparities and inform public health strategies.