Abstract
OBJECTIVE: This study investigated the potential correlation between serum vitamin D levels and the risk of kidney stones. To this end, the National Health and Nutrition Examination Survey (NHANES) database resources from 2007 to 2018 were utilized. The influence of other demographic characteristics, lifestyle habits, and chronic diseases on this relationship was also assessed. METHODS: This study included 59,842 participants from the NHANES survey, and after exclusions, 24,323 individuals with complete data were analyzed. Logistic regression modeling assessed odds ratios (OR) and 95% confidence intervals (CI) between vitamin D levels and kidney stone risk, and multivariable adjustment models were constructed to control for potential confounders. To investigate the dose-response relationship between vitamin D and kidney stones, restricted cubic spline (RCS) modeling was employed. Subgroup and interaction analyses were also conducted. RESULTS: The preliminary analyses indicated a statistically significant positive correlation between vitamin D levels and kidney stone risk before adjustment for potential confounding variables (OR = 1.01, P < 0.001). However, after gradual adjustment for age, gender, race, and multiple lifestyle and chronic diseases, this association became non-significant (OR = 1.00, P = 0.186). Furthermore, RCS analyses demonstrated that the non-linear relationship between vitamin D levels and kidney stone risk was no longer statistically significant after adjustment for confounders. In the subgroup analyses, only slight statistical associations were observed in the subgroups of vigorous exercise and those with diabetes, with no significant differences in the remaining subgroups. CONCLUSION: The present study indicates that serum vitamin D level is not an independent predictor of kidney stone risk. Rather, its effect may be co-regulated by multiple confounding factors. Further research is required to elucidate the precise mechanisms through which vitamin D contributes to kidney stone formation and to consider the combined effects of genetic polymorphisms, dose effects, and other factors.