Related Experiment Video
Updated: Oct 5, 2025

5/6 Nephrectomy Using Sharp Bipolectomy Via Midline Laparotomy in Rats
Published on: April 4, 2025
Ecological meta-analytic study of kidney disease in Italian contaminated sites
Marta Benedetti1, Fabrizio Minichilli2, Maria Eleonora Soggiu1
1Dipartimento Ambiente e Salute, Istituto Superiore di Sanità, Rome, Italy.
Introduction:
Environmental heavy metals exposure has been associated with kidney disease. There is also some evidence that exposure to solvents may be a risk factor for kidney disease. We estimated the risk of hospitalization for kidney diseases (ICD-9 580-586) and chronic kidney disease (CDK, ICD-9 585) in residents in thirty-four Italian National Priority Contaminated Sites (NPCSs) polluted by heavy metals.
Methods:
Random-effects model meta-analyses of SHR (Standard Hospitalization Ratio) computed for each NPCS was performed for all the NPCSs together, and separately, according to the presence/absence of selected industrial activities (petrochemical/refinery and steel plants), and the presence/absence of solvents contamination.
Results:
Pooled SHRs of overall NPCSs were in excess in both genders. Statistically significant excesses were found for CKD in both genders, and for kidney diseases in females, residing in NPCSs with the combined presence of heavy metals and solvents contamination. The pooled SHRs for CKD and kidney diseases were not statistically significant in excess in NPCSs with petrochemical/refinery and steel plants, and only petrochemical/refinery plants.
Conclusions:
The results are suggestive of a possible kidney disease risk in population living in the above-mentioned NPCSs. Epidemiological surveillance and remediation actions in these areas are recommended.
Related Concept Videos
Acute Kidney Injury IV: Diagnostic Studies and Prevention
Chronic Kidney Disease III: Interprofessional Care
Kidney Transplant I: Introduction
Chronic Kidney Disease II: Clinical Manifestations
Chronic Kidney Disease I: Introduction
Drug Dosing in Renal Diseases: Estimation of Glomerular Filtration Rate Based on Serum Creatinine Concentration

