Socioeconomic Status and Clinical Outcomes in Chronic Kidney Disease: Bootstrap Validation of a Simple Indicator

Author:

Pitino Annalisa1,D’Arrigo Graziella2,Marino Carmela2,Pizzini Patrizia2,Caridi Graziella3,Mallamaci Francesca23,Tripepi Giovanni2ORCID,Zoccali Carmine456ORCID

Affiliation:

1. National Research Council of ITALY (CNR), Institute of Clinical Physiology in Rome, 00042 Rome, Italy

2. National Research Council of ITALY (CNR), Institute of Clinical Physiology in Reggio Calabria, 00185 Reggio Calabria, Italy

3. Nephrology and Renal Transplantation Unit, Grande Ospedale Metropolitano, 20126 Reggio Calabria, Italy

4. Renal Research Institute, New York, NY 10065, USA

5. Institute of Molecular Biology and Genetics (Biogem), 21846 Ariano Irpino, Italy

6. Carmine Zoccali IPNET, Associazione Ipertensione Nefrologia Trapianto (IPNET), c/o Nefrologia, Grande Ospedale Metropolitano, 89124 Reggio Calabria, Italy

Abstract

Background: Chronic Kidney Disease (CKD) is a complex health condition that interacts significantly with socioeconomic determinants, particularly income status and education. This study developed a simple indicator of socioeconomic status (SES), which is composed of income status and education in CKD patients, and evaluated its impact on health outcomes in this population. Methods: This study was conducted on 561 CKD patients, stages 2–5. The composite SES score was developed by combining the regression coefficients of income and education as predictors of the study endpoint in a multivariable Cox model, normalizing these coefficients to derive weights, and then using these weights to calculate an individual percentage score based on each person’s income and education. The composed SES indicator was internally validated through bootstrap analysis. Over a median follow-up time of 36 months, we tracked all-cause death and non-fatal cardiovascular events. Results: Both lack of income (p = 0.020) and low educational level (p = 0.034) were independently related to the combined endpoint. Based on these covariates‘ regression coefficients, a composite socioeconomic score considering income and educational level was generated. In a Cox regression model, a 10% increase in this composite risk score entailed a 25% increase in the hazard ratio (HR) of the combined endpoint [HR (10% increase): 1.25], and the internally validated 95% CI ranged from 1.14 to 1.41 (p < 0.001). Conclusions: This study underscores the significant impact of a simple, bootstrap-validated composite SES indicator on CKD patients’ health outcomes. These findings highlight the importance of considering education and socioeconomic factors in managing and treating CKD patients and inform future research and policy considerations for this population.

Publisher

MDPI AG

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