Chronic Kidney Disease

In CKD, Caffeine Could Reduce Mortality Risk

Higher intake of caffeine could help to reduce mortality risk among individuals with chronic kidney disease (CKD), according to the results of a recent study.

 

Previous research has indicated an inverse relationship between coffee consumption and mortality among the general population. However, whether this relationship exists in patients with CKD is uncertain.


READ MORE...

In CKD Patients, Sleep Duration Significantly Affects Quality of Life

CKD/Diabetes Outcomes Improved With Risk Factor Control


To further examine this relationship, researchers examined data from 4863 adults with CDK (defined by an estimated glomerular filtration rate [eGFR] of 15–60 mL/min/1.73 m2 and/or a urinary albumin:creatinine ratio >30 mg/g) from the National Health and Nutrition Examination Survey 199902010. Twenty-four-hour dietary recalls were utilized to evaluate caffeine consumption at baseline. They divided the participants into quartiles by caffeine consumption: <28.2 mg/day (Q1), 28.2–103.0 (Q2), 103.01–213.5 (Q3) and >213.5 (Q4). They also further segmented participants by the source of their caffeine intake.

 

Over a median follow-up of 60 months, 1283 of the participants died. When compared with Q1, the adjusted hazard ratio (HR) for all-cause mortality was 0.74, 0.74, and 0.78 for participants in Q2, Q3, and Q4, respectively. Stages of CKD and urinary albumin:creatinine ratio categories had no observed interaction with caffeine consumption.

 

“Our study showed an inverse association between caffeine and all-cause mortality among participants with CKD,” the researchers concluded.

 

“If these results are to be confirmed by prospective studies, advising these patients to drink more caffeine may reduce their mortality. This would be a simple, clinically beneficial and inexpensive option in patients with CKD”

 

—Michael Potts

 

Reference:

Vieira MB, Magrico R, Dias CV, et al. Caffeine consumption and mortality in chronic kidney disease: a nationally representative analysis [published online September 12, 2018]. NDT. https://doi.org/10.1093/ndt/gfy234.