Login / Signup

Evaluating the American Urologic Association (AUA) dietary recommendations for kidney stone management using the National Health And Nutritional Examination Survey (NHANES).

Kevin Liu KotKevin F LabagnaraJoseph I KimJustin LoloiKavita GuptaIlir AgalliuAlexander C Small
Published in: Urolithiasis (2023)
The objective of this study is to evaluate the conventional dietary recommendations for stone prevention among patients in the National Health and Nutritional Examination Survey (NHANES) and compare dietary components and special diets between stone formers and non-stone formers. We analyzed the NHANES 2011-2018 dietary and kidney condition questionnaires, among 16,939 respondents who were included in this analysis. Dietary variables were selected based on the American Urological Association (AUA) guideline for Medical Management of Kidney Stones and from other studies on kidney stone prevention. Weighted multivariate logistic regression models were used to assess the relationship of dietary food components (categorized into quartiles) and dietary recommendations with kidney stone formation (yes vs no), adjusted for total caloric intake, comorbidities, age, race/ethnicity, and sex. The prevalence of kidney stones was 9.9%. Our results showed association of kidney stones with lower levels of potassium (p for trend = 0.047), which was strongest for < 2000 mg (OR = 1.35; 95% CI 1.01-1.79). Higher vitamin C intake was inversely associated with stone formation (p for trend = 0.012), particularly at daily intake levels between 60 and 110 mg (OR = 0.76; 95% CI 0.60-0.95) and above 110mcg (OR = 0.80; 95% CI 0.66-0.97). There were no associations between other dietary components and kidney stone formation. Higher levels of dietary vitamin C and potassium intake may be indicated for stone prevention and warrants further investigation.
Keyphrases
  • healthcare
  • editorial comment
  • body mass index
  • risk factors
  • magnetic resonance imaging
  • risk assessment
  • climate change
  • cross sectional
  • network analysis