Association Between Ultraprocessed Food Consumption and Risk of Incident CKD: A Prospective Cohort Study

Abstract

Rationale & objective: Ultraprocessed foods have become readily available in the global food supply in the past few decades. Several adverse health outcomes have been linked with higher consumption of ultraprocessed foods. However, the impact of ultraprocessed foods on chronic kidney disease (CKD) risk remains unknown.

Study design: Prospective cohort study.

Setting & participants: 14,679 middle-aged adults without CKD at baseline in the Atherosclerosis Risk in Communities (ARIC) study.

Exposure: Ultraprocessed foods consumption (servings per day) calculated using dietary data collected via a food frequency questionnaire at visit 1 and visit 3.

Outcome: Incident CKD defined as estimated glomerular filtration rate (eGFR) < 60 mL/min/1.73 m² accompanied by ≥25% eGFR decline, CKD-related hospitalization or death, or kidney failure with kidney replacement therapy.

Analytical approach: Multivariable-adjusted Cox proportional hazards models were used to assess the association between ultraprocessed foods consumption and CKD. Restricted cubic splines were used to examine the shape of the association.

Results: During a median follow-up period of 24 years, there were 4,859 cases of incident CKD. The incidence rate for the highest quartile of ultraprocessed foods consumption was 16.5 (95% CI, 15.6-17.4) per 1,000 person-years and 14.7 (95% CI, 13.9-15.5) per 1,000 person-years for the lowest quartile of consumption. After adjusting for a range of confounders including lifestyle factors, demographic characteristics, and health behaviors, participants in the highest quartile of ultraprocessed foods consumption had a 24% higher risk (HR, 1.24 [95% CI, 1.15-1.35]) of developing CKD compared with those in the lowest quartile. There was an approximately linear relationship observed between ultraprocessed food intake and risk of CKD. By substituting 1 serving of ultraprocessed foods with minimally processed foods, there was a 6% lower risk of CKD observed (HR, 0.94 [95% CI, 0.93-0.96]; P < 0.001).

Limitations: Self-reported data and residual confounding.

Conclusions: Higher ultraprocessed foods consumption was independently associated with a higher risk of incident CKD in a general population.

Keywords: ARIC Study; NOVA classification; chronic kidney disease (CKD); diet and nutrition; dietary intake; end-stage renal disease (ESRD); epidemiology; food frequency questionnaire (FFQ); incident CKD; modifiable risk factor; nutritional quality; ultraprocessed foods.

Figure 1.

Flowchart for the selection of the analytic sample from the Atherosclerosis Risk in Communities (ARIC) Study. Number of participants excluded for each covariate: age (n = 0), body mass index (n = 11), physical activity score (n = 44), smoking status (n = 13), drinking status (n = 37), education level (n = 18), diabetes status (n = 119), hypertension status (n = 79), eGFR level (n = 27), serum cholesterol level (n = 104); Abbreviations: eGFR, estimated glomerular filtration rate; FFQ, food frequency questionnaire

Figure 2.

Restricted cubic spline of the association between ultra-processed food consumption and risk of incident CKD. The grey histogram shows the distribution of ultra-processed food consumption. The black solid line represents the adjusted hazard ratios for incident CKD, modeled using restricted cubic splines with 4 knots at the 5^th, 35^th, 65^th, and 95^th percentiles. The reference level was set at the 25^th percentile (3.87 servings/day). The black dashed lines represent 95% confidence intervals. The model was adjusted for age, sex, race-center, total energy intake, education level, smoking status, and physical activity score. Abbreviations: CI, confidence interval; CKD, chronic kidney disease; HR, hazard ratio.

Figure 3.

Risk of incident CKD associated with ultra-processed food consumption according to subgroups of the study population. HRs and 95% CI were presented for quartile 4 versus quartile 1 of ultra-processed food consumption. The model was adjusted for age, sex, race-center, total energy intake, education level, smoking status, and physical activity score. Abbreviations: BMI, body mass index; CI, confidence interval; CKD, chronic kidney disease; HR, hazard ratio.