Chronic Kidney Disease in Agricultural Communities

Abstract

Patients residing in agricultural communities have a high risk of developing chronic kidney disease. In the Great Plains, geo-environmental risk factors (eg, variable climate, temperature, air quality, water quality, and drought) combine with agro-environmental risk factors (eg, exposure to fertilizers, soil conditioners, herbicides, fungicides, and pesticides) to increase risk for toxic nephropathy. However, research defining the specific influence of agricultural chemicals on the progression of kidney disease in rural communities has been somewhat limited. By linking retrospective clinical data within electronic medical records to environmental data from sources like US Environmental Protection Agency, analytical models are beginning to provide insight into the impact of agricultural practices on the rate of progression for kidney disease in rural communities.

Introduction

In the United States,1 in 7 adults has some form of chronic kidney disease (CKD).¹ The burden of disease is enormous, and the number of patients with end-stage renal disease is increasing. Patients with early-stage CKD need to be identified sooner, and novel interventions need to be deployed to attenuate progression to end-stage renal disease.² With the widespread implementation of electronic medical records (EMR), accurate risk-prediction models are now capable of decreasing the lag in the time to diagnosis for all stages of CKD. However our ability to identify individual patients at increased risk for progressing more rapidly remains suboptimal. Although advances are being made in genomics, proteomics, and metabolomics, much more work is needed to characterize the impact of environmental factors beyond the well-known risk determinants of obesity, diabetes, and hypertension.

Over the last decade, a new renal disease entity named “chronic kidney disease of unknown etiology” (CKD_u) has emerged in some agricultural communities.³ Although CKD_u is now contributing to significant morbidity and mortality worldwide, this condition remains largely unrecognized by many health care providers. The hallmark of CKD_u is that it does not follow typical patterns of age distribution nor is there a direct association with diabetes or hypertension. Rather, CKD_u tends to occur in young men working in an agricultural setting. Although dehydration and recurrent episodes of acute kidney injury can contribute to CKD_u, they are not sufficient to explain this phenomenon in its entirety.³ We, therefore, review the development of risk-prediction models in rural communities, and we explore approaches to the integration of environmental data in these models.