Globally, there is increasing recognition that agricultural workers are at risk for chronic kidney disease of unknown etiology (CKDu). Recurrent heat exposure, physical exertion, dehydration, muscle damage, and inflammation are hypothesized to contribute to the development of CKDu, but the relative importance of these processes and the interactions among them remain unclear. Moreover, there is a need to identify biomarkers that could distinguish individuals who are at greatest risk for kidney damage to target preventative interventions for CKDu. In this study, we evaluated dehydration and markers of inflammation, muscle damage, and renal function in agricultural workers at a non-workday baseline assessment. Urine specific gravity and kidney function were measured before and after work shifts on three subsequent days, and heat index, core body temperature, and heart rate were monitored during the work shifts. A combination of direct comparisons and machine learning algorithms revealed that reduced levels of uromodulin and sodium in urine and increased levels of interleukin-6 and C-reactive protein in serum were indicative of dehydration at baseline, and that dehydration, high body mass index, reduced urine uromodulin, and increased serum interleukin-6, C-reactive protein, and lipopolysaccharide-binding protein at baseline were predictive of acute kidney injury on subsequent workdays. Our findings suggest a method for identifying agricultural workers at greatest risk for kidney injury and reveal potential mechanisms responsible for this process, including pathways overlapping in dehydration and kidney injury. These results will guide future studies confirming these mechanisms and introducing interventions to protect kidney health in this vulnerable population.
Keywords: acute kidney injury; agricultural workers; chronic kidney injury of unknown etiology; classification tree; dehydration; inflammation.