Background

Chronic kidney disease of unknown etiology (CKDu) is a leading cause of premature mortality in Mesoamerica, predominantly affecting young adult males working in agriculture. In Mesoamerica countries such as Nicaragua, Guatemala, and El Salvador, this disease has significant social and economic impacts on rural communities where it causes acute kidney failure among young, working-age men. Patients of CKDu do not experience typical end-stage renal diseases conditions, such as hypertension, diabetes, and glomerular disease (Sanchez Polo et al., 2020).

The number of deaths caused by CKDu increased by 40% from 2005 to 2009 in Nicaragua alone. Countries in Mesoamerica are also consistently ranked among the top 10 countries with the highest overall mortality from kidney disease. In 2012, an estimated 20,000 deaths were attributable to this disease in Mesoamerica. Other countries such as Sri Lanka, Egypt, and India have also reported similar cases of chronic kidney disease with epidemiological characteristics similar to CKDu in Mesoamerica (Ramirez-Rubio et al, 2013).

Researchers have identified possible causes such as heat stress, dehydration, and environmental toxins (Jayasumana et al., 2015). Some have also proposed that no single exposure can be attributable to cause CKDu on such a large scale. Instead, multiple factors must be simultaneously at work to cause initial mild kidney injuries, and other factors are then responsible for worsening kidney functions, eventually resulting in kidney failure (Pearce and Caplin, 2018).

I got involved with this project in the summer of 2022. I was looking for an Honors project opportunity, so my advisor Dr. Brianna Heggeseth introduced me to this project. What amazes me about this project is how dedicated our collaborators are. Dr. Ben Caplin and Dr. Marvin Quiroz Gonzalez are nephrologists working in the UK and Nicaragua. They started the project in 2013 and have been collecting data since then.

Data and Statistical Methodology

A Hidden Markov model is used to model kidney health. The kidney health states are hidden here. Although the eGFR values are generally referred to as a reflection of kidney function, a low eGFR does not necessarily mean unhealthy kidney function, and the kidney health state is not directly observable. I categorized kidney health into three states: healthy, borderline, and unhealthy. The exposures, such as sugarcane work and agrichemical exposure, will affect the transition probabilities between the states.

Our data came from a 7-year community-based longitudinal study. It is collected annually from the same individuals in Leon and Chinandega departments, rural Nicaragua communities. All participants are healthy in the beginning with no pre-existing disease.

The data is from questionnaires on exposure variables such as sugarcane work, agrichemical exposure, and alcohol. All these exposures are binary. If the participant had exposure to the variable between now and the last time they filled out the questionnaire, they would indicate one and zero otherwise. A blood sample is also collected to measure the eGFR (estimated glomerular filtration rate), an estimated measure of how the kidney filters waste and often interpreted as a measure of kidney function.

Results

Working in the sugarcane field negatively affects kidney health, making it less likely to transition from a borderline to a healthy state. Those who work in the sugarcane field are more likely to be exposed to several other factors, such as sunstroke and exposure to agrichemicals (Johnson et al., 2019). Among those who work in sugarcane, 86% are male compared to 72% in those who do not, 21% suffer from sunstroke compared to 13% who did not, and 39% are exposed to agrichemicals compared to 15% who did not.

Regular alcohol consumption harms kidney health, making it less likely to transition from a borderline to a healthy state. Alcohol dehydrates the body, and the drying affects the kidney’s function of filtering water in the body. Drinking alcohol is also associated with liver disease. The liver controls blood flow to the kidney, balancing it at a level that allows the kidney to filter body waste at the optimal level (Lai et al., 2019).

Smoking regularly also harms kidney health. Smoking also controls the blood flow to many major body organs, including the kidney (Yacoub et al., 2010). Thus smoking could worsen existing kidney problems. Male participants disproportionately participate in alcohol drinking and smoking. 93% and 99% of the participants who drink alcohol and smoke regularly are male.

Discussion

We are restricted in exploring some exposure variables due to Hidden Markov model computation issues. The significant exposures, sugarcane work, regular alcohol consumption and smoking, are confounded by Sex. For example, if the participant is male, he is more likely to work in the sugarcane field, regularly consume alcohol and smoke. When a male participant experiences a drop in kidney health, it is difficult to determine the specific cause of this drop. Being male indicates a higher risk of all three exposures significantly associated with worsening kidney health. Possible solutions include running sex-stratified analysis and incorporating multiple covariances into the model.

Other variables not captured by the data may also affect kidney health. Regions traditionally affected by CKDu are where the primary economic focus is on paddy and sugarcane farming. However, people from outside these regions are still affected by the disease. The amount of urinary cadmium and lead excretion correlate strongly with eGFR values, indicating that environmental pollution instead of occupational exposure is the cause of CKDu (Wijewickrama et al., 2022). Moreover, the effect of environmental pollution is hard to determine, since people could exhibit a variety of reactions. Additionally, there is no current global definition of CKDu. Water sources, work procedures, environmental exposures, and safety procedures for agrichemicals differ widely by location (Weaver et al., 2015).

References

Jayasumana, C., Paranagama, P., Agampodi, S. et al. Drinking well water and occupational exposure to Herbicides is associated with chronic kidney disease, in Padavi-Sripura, Sri Lanka. Environ Health 14, 6 (2015). https://doi.org/10.1186/1476-069X-14-6

Johnson, Richard J., et al. “Chronic Kidney Disease of Unknown Cause in Agricultural Communities.” New England Journal of Medicine, vol. 380, no. 19, 2019, pp. 1843–1852., https://doi.org/10.1056/nejmra1813869. Weaver, Virginia M et al. “Global dimensions of chronic kidney disease of unknown etiology (CKDu): a modern era environmental and/or occupational nephropathy?.” BMC nephrology vol. 16 145. 19 Aug. 2015, doi:10.1186/s12882-015-0105-6

Lai, Yun-Ju et al. “Alcohol Consumption and Risk of Chronic Kidney Disease: A Nationwide Observational Cohort Study.” Nutrients vol. 11,9 2121. 6 Sep. 2019, doi:10.3390/nu11092121

Oriana Ramirez-Rubio, Michael D McClean, Juan José Amador, Daniel R Brooks, An epidemic of chronic kidney disease in Central America: an overview, Postgraduate Medical Journal, Volume 89, Issue 1049, March 2013, Pages 123–125, https://doi.org/10.1136/postgradmedj-2012-201141rep

Pearce, Neil, and Ben Caplin. “Let’s Take the Heat out of the CKDU Debate: More Evidence Is Needed.” London School of Hygiene and Tropical Medicine, London School of Hygiene and Tropical Medicine, Aug. 2018, https://researchonline.lshtm.ac.uk/id/eprint/4651317/1/Pearce-Caplin-2019-CKDu-debate.pdf.

Sanchez Polo, Vicente et al. “Mesoamerican Nephropathy (MeN): What We Know so Far.” International journal of nephrology and renovascular disease vol. 13 261-272. 22 Oct. 2020, doi:10.2147/IJNRD.S270709

Wijewickrama, Eranga S., et al. “Prevalence of CKD of Unknown Etiology and Its Potential Risk Factors in a Rural Population in Sri Lanka.” Kidney International Reports, vol. 7, no. 10, 2022, pp. 2303–2307., https://doi.org/10.1016/j.ekir.2022.07.012.

Yacoub, Rabi et al. “Association between smoking and chronic kidney disease: a case control study.” BMC public health vol. 10 731. 25 Nov. 2010, doi:10.1186/1471-2458-10-731

Connie Zhang

Hi, my name is Connie! I’m a senior Statistics majors with a particular interest in biostatistics. On campus I’m involved as an international student mentor and blood drive coordinator. Outside of school, I enjoy reading, hanging out with my cat, and eating good food. After Macalester, I will be pursuing my Biostatistics PhD at the University of Washington.

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