Inverse association between prognostic nutritional index and kidney stone prevalence: A population-based study

Abstract

Background: Kidney stones frequently occur due to metabolic disorders, dietary habits, and lifestyle influences. The Prognostic Nutritional Index, which reflects an individual's nutritional condition, might be associated with kidney stone prevalence. This study examines the association between PNI and kidney stone prevalence in US adults.

Methods: The study used data from the National Health and Nutrition Examination Survey database from 2009-2018 and excluded pregnant women, and individuals who lacked data on kidney stones, or had incomplete Prognostic Nutritional Index data. Independent associations between Prognostic Nutritional Index and kidney stones were investigated by multivariate logistic regression and subgroup analyses, in addition to exploring nonlinear associations using smoothed curves and threshold effects.

Results: A total of 13,835 participants aged ≥ 20 years were included, with a kidney stone prevalence of 8.48%. An inverse association was observed between the Prognostic Nutritional Index and kidney stone prevalence (OR = 0.97, 95% CI = 0.96-0.98, P < 0.001). This relationship was not significantly modified by race, education, marital status, or comorbidities such as hypertension, diabetes, and hyperlipidemia. However, sex and total cholesterol levels influenced the association. Stratified analysis showed a significant negative association in men (OR = 0.98, 95% CI = 0.96-0.99, P = 0.031), but not in women. A nonlinear relationship was identified in individuals with total cholesterol ≥ 5.2 mmol/L, with a significant negative association below the inflection point of 57 (OR = 0.96, P = 0.012) and a positive association above it (OR = 1.11, P = 0.03). These findings suggest that the Prognostic Nutritional Index is inversely associated with kidney stones, particularly in men and those with high cholesterol levels.

Conclusion: The Prognostic Nutritional Index was negatively associated with the risk of kidney stones, particularly in men and individuals with high cholesterol levels below the identified inflection point, suggesting that tailored nutritional management may be crucial for these subgroups.

Fig 1. Flowchart of the selection of participants from NHANES 2009–2018.

Fig 2. Subgroup analysis of the association between PNI and kidney stones.

Abbreviation: PNI, Prognostic nutritional index; PIR, the ratio of family income to poverty; TC, Total cholesterol; HbA1c, Glycosylated hemoglobin; eGFR, Estimated Glomerular filtration rate; BMI, Body mass index.

Fig 3. A linear relationship between PNI and kidney stones by the generalized additive model.

Age, gender, race, educational level, BMI, Sedentary time, Marital status, PIR, Hypertension, Diabetes mellitus, Hyperlipidemia, Coronary heart disease, Smoking history, Urea nitrogen, Triglyceride, HbA1c, TC, eGFR, Protein intake, Sodium intake, and Potassium intake were adjusted. Abbreviation: OR, Odds ratio; 95% CI, 95% confidence interval; PNI, Prognostic nutritional index; PIR, the ratio of family income to poverty; TC, Total cholesterol; HbA1c, Glycosylated hemoglobin; eGFR, Estimated Glomerular filtration rate; BMI, Body mass index.

Fig 4. Adjusted dose-response relationship between PNI and kidney stone incidence stratified by total cholesterol levels.

Age, gender, race, educational level, BMI, Sedentary time, Marital status, PIR, Hypertension, Diabetes mellitus, Hyperlipidemia, Coronary heart disease, Smoking history, Urea nitrogen, Triglyceride, HbA1c, eGFR, Protein intake, Sodium intake, and Potassium intake were adjusted.

Fig 5. Adjusted dose-response relationship between PNI and kidney stone incidence stratified by sex.

Age, race, educational level, BMI, Sedentary time, Marital status, PIR, Hypertension, Diabetes mellitus, Hyperlipidemia, Coronary heart disease, Smoking history, Urea nitrogen, Triglyceride, HbA1c, TC, eGFR, Protein intake, Sodium intake, and Potassium intake were adjusted.