Uric acid levels mediate the association between four dietary indices and kidney stones in US adults: A cross-sectional study of NHANES 2007–2018

Jinlong Cao; Tianyuan Zhai; Lingyu Guo; Yue Chong; Qi Chen; Qian Wang; Delai Fu; Li Xue; Feng Li

doi:10.1371/journal.pone.0339839

. 2026 Jan 2;21(1):e0339839. doi: 10.1371/journal.pone.0339839

Uric acid levels mediate the association between four dietary indices and kidney stones in US adults: A cross-sectional study of NHANES 2007–2018

Jinlong Cao ¹, Tianyuan Zhai ¹, Lingyu Guo ¹, Yue Chong ¹, Qi Chen ¹, Qian Wang ¹, Delai Fu ¹, Li Xue ^1,^*, Feng Li ^1,^*

Editor: Yogesh Kumar Jain²

PMCID: PMC12758690 PMID: 41481627

Abstract

Background

Diet and uric acid are closely linked to the formation of kidney stones. However, the specific dietary indices associated with kidney stone risk and the mediating role of uric acid remain unclear. This study investigates the association between four dietary indices and kidney stone risk while exploring the mediating role of uric acid.

Methods

Data were obtained from the National Health and Nutrition Examination Survey (NHANES). Four dietary indices were calculated: the Mediterranean Diet (MED), Healthy Eating Index-2020 (HEI-2020), Alternate Healthy Eating Index (AHEI), and Dietary Approaches to Stop Hypertension (DASH). Univariate logistic regression analysis and restricted cubic splines (RCS) curve were used to analyze the single effect of dietary index and kidney stones. Weighted Quantile Sum (WQS) and Bayesian Kernel Machine Regression (BKMR) to visualize the mixed effects of multiple dietary indices and kidney stone risk. Finally, mediation analyses were employed to assess associations and mediation effects.

Results

Among 25,421 participants, 2,470 had a history of kidney stones. All four dietary indices showed a significant negative association with kidney stone risk, with MED and HEI-2020 showing the strongest effects. WQS regression results indicated that the mixed effects of the four dietary indices were negatively correlated with kidney stones, with the highest weight attributed to HEI2020 (49.2%), followed by DASH (26.4%), MED (21.8%), and AHEI (2.9%). BKMR analysis revealed a negative exposure-response trend for each dietary indices to the risk of kidney stones and HEI2020, DASH, MED, and AHEI are negative related with kidney stones at all three quantiles. Mediation analysis revealed that uric acid mediated the relationship between dietary indices and kidney stone risk, with mediation proportions of 25.56% (MED), 12.14% (AHEI), 5.88% (DASH), and 2.52% (HEI-2020).

Conclusion

Healthy dietary patterns are associated with a reduced risk of kidney stones, partially mediated by uric acid levels.

1. Introduction

Kidney stone is one of the common urinary system diseases worldwide, and the prevalence is increasing worldwide. In the United States, the prevalence of kidney stones has long been around 10% in the adult population, with a higher incidence among males compared to females [1–3]. The formation of kidney stones is influenced by a variety of common factors. Underlying conditions such as obesity, gout, asthma, and diabetes can all contribute to an increased incidence of kidney stones [4–6]. Furthermore, inadequate fluid intake [7], a high-salt diet [8], diets rich in animal protein, and low-fiber dietary habits can elevate the risk of stone formation [9]. Therefore, it is important to investigate the diet-related factors associated with the occurrence of kidney stones and develop effective prevention strategies.

A healthy balanced diet is very essential to prevent kidney stones. Dietary indices are widely used tools to evaluate overall diet quality and its relation to disease. Previous studies have shown that higher Dietary Inflammatory Index (DII) scores and increased intake of pro-inflammatory diets are associated with an increased incidence and recurrence of kidney stones [10]. Niloofar et. al found that a higher Dietary Insulin Load (DIL) is directly related to the likelihood of kidney stones [11]. Additionally, a large cohort study in China indicated that adhering to a balanced dietary pattern, rather than a plant-based diet, is associated with a lower risk of kidney stones [12]. Of the main dietary indices, four well-established indices—the Mediterranean Diet (MED), the Healthy Eating Index-2020 (HEI-2020), the Alternate Healthy Eating Index (AHEI), and the Dietary Approaches to Stop Hypertension (DASH)—emphasize higher intake of fruits, vegetables, whole grains, and plant-based proteins, and lower intake of red meat, sodium, and saturated fat [13,14]. These patterns are known to improve metabolic health and reduce oxidative stress.

Uric acid is a key biochemical factor in stone formation, especially for urate and calcium-containing stones. Diet strongly influences uric acid metabolism: high-purine animal protein, fructose-rich beverages, and alcohol increase uric acid levels, whereas plant-based and low-fat diets reduce them [15]. Therefore, uric acid may act as a mediator linking dietary patterns and kidney stone risk, but the specific mechanisms underlying this process still lack adequate evidence.

Given these mechanisms, we hypothesized that healthy dietary patterns might reduce the risk of kidney stones in part through modulation of uric acid levels. Although several previous studies have investigated individual dietary indices (e.g., DASH or MED) using NHANES or cohort data [16,17], few have comprehensively compared multiple healthy dietary indices within the same population while examining uric acid as a biological mediator. This integrative approach may provide new insight into the mechanisms linking diet and stone formation. Our study uncovers potential associations between healthy dietary patterns and kidney stones, and to provide a scientific basis for the prevention and treatment of kidney stones through dietary interventions.

2. Methods

2.1 Study population and design

The raw data for this study were obtained from the NHANES III database (https://www.cdc.gov/nchs/nhanes/), with the study population and design conducted by the Centers for Disease Control and Prevention (CDC) and the National Center for Health Statistics (NCHS). The data from NHANES has been approved by the Institutional Review Board of the NCHS, and all participants provided written informed consent. We included data from six cycles (2007–2018), a total of 59,842 participants, as these cycles provided both kidney stone history and dietary and uric acid test data. Participants were excluded if they were under 18 years old and lacked kidney stone information (25,072 individuals), lacked dietary information (7,923 individuals), and lacked uric acid data (1,335 individuals). In the end, 25,421 participants were included in this study, with the detailed screening process shown in Fig 1.

2.2 Dietary indices

The raw data of the four dietary indices was assessed using 48-hour dietary recall data. Dietary intake data were used to estimate the types and quantities of foods and beverage consumed during the 48-hour prior to the interview and to estimate the intake of energy, nutrients, and other food components from these foods and beverages. These data were collected through two retrospective interviews. Nutrients and energy for each food or beverage were calculated using the Food and Nutrition Database for Dietary Studies (FNDDS), The United States Department of Agriculture Food Pattern Equivalents Database (FPED) guideline was used for food group classification. Our analysis is grounded in data from four widely recognized dietary pattern indices that serve as proxies for dietary quality: MED, HEI2020, AHEI and DASH diets. The MED is a healthy dietary pattern characterized by increased consumption of legumes, vegetables, fruits, olive oil, whole grain grains, and nuts. It also includes moderate consumption of fish and red wine, while limiting consumption of red meat products and saturated fatty acids. The HEI-2020 assesses diet quality according to the Dietary Guidelines for Americans 2020−2025–13 food groups or nutrient components, with a total score of 100, and higher scores indicate better diet quality. It provides a comprehensive assessment of dietary habits and the complex effects of diet on disease risk and metabolic disorders. The AHEI was extended from HEI-2010 to include more dietary factors related to chronic disease risk, based on the intake scores of 11 foods and nutrients. The DASH diet was originally developed by the National Heart, Lung, and Blood Institute (NHLBI) as a dietary model for the prevention and control of hypertension and is now considered to be one of the ideal dietary options for all adults. The four dietary indices were calculated with the use of the dietaryindex R package [18].

2.3 Definition of kidney stones

The Kidney Conditions – Urology questionnaire was directed at adults aged 20 years and older, which includes questions about a history of kidney stones. Survey participants who answered yes to ‘(KIQ026) Have you/Has sample person (SP) ever had a kidney stone?’ were considered to have a history of kidney stones. And no was considered to no kidney stones history. Don’t known and refused were excluded.

2.4 Mediation variables assessment

A standard biochemistry test was conducted by trained laboratory technicians, and uric acid concentration was measured using a timed endpoint method. Detailed instructions about analytical methodologies, principles, and operating procedures are shown in the NHANES Laboratory Method Files.

2.5 Covariate assessment

Potential covariates were identified a priori based on a literature review [8,10], including age, Body Mass Index (BMI), cotinine (substitute for smoking), gender (male/female), marital status (Divorced/ Living with partner/ Married/ Never married/ Separated/ Widowed), alcohol, race (Mexican American/ Non-Hispanic Black/ Non-Hispanic White/ Other Hispanic/ Other Race – Including Multi-Racial), education (College Graduate or above/ High School Grad/ Less Than 9th Grade/ Some College or AA degree), hypertension and Diabetes. Cotinine content, it would be more accurate to quantify the level of human exposure to tobacco smoke [19,20]. Alcohol status was categorized into five groups: never consumption (<12 drinks in lifetime), former consumption (≥12 drinks in 1 year and did not drink last year, or did not drink last year but drank ≥12 drinks in lifetime), mild consumption (1 drinks/d for female and 2 drinks/d for male), moderate consumption (2 drinks/d for female and 3 drinks/d for male), and heavy consumption (3 drinks/d for female and 4 drinks/d for male) [21].

2.6 Statistical analysis

Statistical analyses were performed according to the NHANES data analysis reporting guidelines, and all analyses were performed on a weighted treatment basis. In data processing, continuous data were expressed mean ± standard deviation and analyzed by t-tests, categorical data were expressed as proportion and analyzed by χ2 test.

To assess the robustness of the associations between dietary indices and kidney stones, three logistic regression models were constructed. The crude model estimated the unadjusted association between each dietary index and kidney stone risk. Model 1 was adjusted for demographic factors, including age, sex, and race. Model 2 was further adjusted for socioeconomic and clinical variables, including education level, marital status, BMI, cotinine, alcohol consumption, hypertension, and diabetes. This stepwise modeling approach was used to determine whether the observed associations were independent of demographic and clinical confounding factors. Restricted cubic spline (RCS) models were used to determine a possible dose-response relationship between dietary index and kidney stones. The weighted quantile sum (WQS) regression model explored the association between multiple dietary indices and kidney stones. The magnitude of the weights shows the contribution of each dietary index to the WQS index, with higher values indicating greater effects. Data were tested and validated using 40% and 60% stratified random samples, with 1000 bootstrap iterations [22]. Given the potential nonlinear and non-additive relationships between dietary index scores, Bayesian kernel machine regression (BKMR) was used to visualize the association between multiple dietary index scores and kidney stone risk [23]. Finally, we evaluated the mediation effect of four dietary indices on the effect of kidney stones through uric acid.

R (version 4.2.1) was used for all statistical analyses, and P < 0.05 (two-side test) were considered to statistical significance. WQS was performed using the gWQS package, BKMR was performed using the BKMR package, and mediation effect analysis was performed using the Mediation package (Table 1).

Table 1. Baseline characteristics of included participants.

Characteristics	Overall	Non-kidney stone	Kidney stone	P
Number	25421	22951	2470
Age (Years)	50.26 ± 17.52	49.58 ± 17.56	56.50 ± 15.87	<0.001
Age category				<0.001
< 60	16665 (65.6%)	15383 (67.0%)	1283 (51.90%)
≥60	8756 (34.4%)	7569 (33.0%)	1187 (48.10%)
Gender				<0.001
Female	11034 (52.5%)	10127 (53.5%)	907 (43.8%)
Male	9967 (47.5%)	8802 (46.5%)	1165 (56.2%)
BMI (kg/m2)	29.48 ± 7.01	29.36 ± 7.02	30.52 ± 6.77	<0.001
BMI category				<0.001
< 18.5	364 (1.4%)	347 (1.5%)	17 (0.7%)
18.5-24.9	6566 (26.1%)	6109 (26.9%)	457 (18.7%)
25.0-29.9	8290 (32.9%)	7466 (32.8%)	824 (33.7%)
≥30	9962 (39.6%)	8818 (38.8%)	1144 (46.8%)
Race				<0.001
Mexican American	3317 (15.7%)	3055 (16.0%)	262 (12.5%)
Non-Hispanic Black	4192 (19.8%)	3933 (20.6%)	259 (12.4%)
Non-Hispanic White	9317 (44.0%)	8110 (42.5%)	1207 (57.8%)
Other Hispanic	2211 (10.4%)	1996 (10.5%)	215 (10.3%)
Other Race	2126 (10.0%)	1981 (10.4%)	145 (6.9%)
Education				0.022
Less Than 9th Grade	1997 (9.4%)	1804 (9.5%)	193 (9.2%)
9-11th Grade	2841 (13.4%)	2549 (13.4%)	292 (14.0%)
High School Grad	4906 (23.2%)	4431 (23.2%)	475 (22.7%)
Some College or AA degree	6338 (29.9%)	5654 (29.6%)	684 (32.8%)
College Graduate or above	5060 (23.9%)	4617 (24.2%)	443 (21.2%)
Refused	6 (0.0%)	6 (0.0%)	0 (0.0%)
Missing	15 (0.1%)	14 (0.1%)	1 (0.0%)
Marital Status				<0.001
Married	11177 (52.8%)	9961 (52.2%)	1216 (58.2%)
Living with partner	1688 (8.0%)	1562 (8.2%)	126 (6.0%)
Divorced	2364 (11.2%)	2075 (10.9%)	289 (13.8%)
Separated	695 (3.3%)	630 (3.3%)	65 (3.1%)
Never married	3601 (17.0%)	3405 (17.9%)	196 (9.4%)
Widowed	1631 (7.7%)	1436 (7.5%)	195 (9.3%)
Refused	6 (0.0%)	5 (0.0%)	1 (0.0%)
Missing	1 (0.0%)	1 (0.0%)	0 (0.0%)
HBP				<0.001
No	13360 (63.1%)	12351 (64.7%)	1009 (48.3%)
Yes	7779 (36.8%)	6702 (35.1%)	1077 (51.6%)
Missing	24 (0.1%)	22 (0.1%)	2 (0.1%)
Diabetes				<0.001
No	17823 (84.2%)	16276 (85.3%)	1547 (74.1%)
Borderline	520 (2.5%)	454 (2.4%)	66 (3.2%)
Yes	2809 (13.3%)	2336 (12.2%)	473 (22.7%)
Missing	11 (0.1%)	9 (0.0%)	2 (0.1%)
Cotinine (ng/mL)	55.57 ± 127.20	54.49 ± 125.57	65.39 ± 140.91	<0.001
Alcohol				<0.001
Never	4174 (19.9%)	3771 (19.9%)	403 (19.4%)
Former	1020 (4.9%)	911 (4.8%)	109 (5.3%)
Mild	7900 (37.6%)	7040 (37.2%)	860 (41.5%)
Moderate	3673 (17.5%)	3334 (17.6%)	339 (16.4%)
Heavy	4234 (20.2%)	3873 (20.5%)	361 (17.4%)
MED	3.47 ± 1.37	3.48 ± 1.37	3.37 ± 1.34	<0.001
HEI2020	51.52 ± 12.04	51.64 ± 12.09	50.37 ± 11.54	<0.001
AHEI	38.53 ± 11.49	38.59 ± 11.53	38.02 ± 11.07	0.032
DASH	22.37 ± 5.01	22.40 ± 5.04	22.08 ± 4.80	0.005
Uric acid (mg/dL)	5.45 ± 1.45	5.43 ± 1.44	5.67 ± 1.52	<0.001

Open in a new tab

Mean ± SD for continuous variables, % for categorical variables, The two columns of data, Age (Years) and BMI (kg/m²), have the minimum and maximum values indicated within the brackets. BMI, body mass index; HBP, hypertension; MED, Mediterranean Diet; HEI2020, Healthy Eating Index-2020; AHEI, Alternate Healthy Eating Index; DASH, Dietary Approaches to Stop Hypertension.

3. Results

3.1 Baseline characteristics of the participants

3.2 Association between dietary index and risk of kidney stones

To explore the association between individual dietary indices and the risk of kidney stones, we performed univariate logistic regression with adjustment for relevant confounders on the basis of the presence or absence of kidney stones. The results are shown in Table 2. After adjusting for confounding variables, the risk of kidney stones decreased with increasing scores on all four dietary indices, with AHEI (OR:0.992, 95% CI: 0.990–0.994), DASH (OR:0.976, 95% CI: 0.970–0.991), HEI2020 (OR:0.989, 95% CI: 0.987–0.991), MED (OR:0.941, 95% CI:0.904–0.979), all P < 0.05. This suggests that a healthier diet is important for the prevention of kidney stones.

Table 2. Multiple logistic regression analysis between four dietary indices and kidney stones.

Variable	Crude model		Model 1		Model 2
Variable	OR [95% CI]	p-value	OR [95% CI]	p-value	OR [95% CI]	p-value
AHEI	0.995 (0.993, 0.997)	<0.001	0.988 (0.986, 0.990)	0.001	0.992 (0.990, 0.994)	0.003
DASH	0.985 (0.975, 0.995)	<0.001	0.965 (0.957, 0.974)	<0.001	0.976 (0.970, 0.982)	<0.001
HEI2020	0.990 (0.988, 0.992)	<0.001	0.984 (0.982, 0.986)	<0.001	0.989 (0.987, 0.991)	<0.001
MED	0.929 (0.863, 0.999)	<0.001	0.904 (0.870, 0.939)	<0.001	0.941 (0.904, 0.979)	0.001

Open in a new tab

Crude model: no covariates were adjusted.

Model 1: sex, age, race, educational level, and marital status were adjusted.

Model 2: model 1 + BMI, Cotinine, Alcohol drink, Diabetes and Hypertension (HBP) were fully adjusted.

3.3 Non-linearity and threshold effect analysis between dietary index and risk of kidney stones

RCS curves were used to examine potential nonlinear associations in the relationship between the four dietary indices and the likelihood of kidney stones, and the results are shown in Fig 2. The overall associations between the four dietary indices (AHEI, DASH, HEI2020, and MED) and kidney stone risk were all statistically significant (all P-overall < 0.001). The HEI2020 and MED with the kidney stone risk shows a linear trend (P value for Nonlinear >0.05), while the AHEI and DASH with the kidney stone risk exhibit nonlinear trends (P value for Nonlinear <0.05). Of which, AHEI displayed an inverted U-shaped association with kidney stone risk, with the inflection point occurring at AHEI index scores: 37.73. DASH exhibited an inverted U-shaped association with kidney stone risk, with the inflection point occurring at DASH index scores: 21.96.

Fig 2 — (A) Nonlinear association between AHEI index and the risk of kidney stone. (B) Nonlinear association between DASH index and the risk of kidney stone. (C) Nonlinear association between HEI2020 index and the risk of kidney stone. (D) Nonlinear association between MED index and the risk of kidney stone. OR: odds ratio.

3.4 Association of mixed effects of dietary index with kidney stones evaluated by WQS

We performed Pearson correlation analysis on the four dietary indices and found significant positive correlations among the four dietary indices (as shown in Fig 3A). Fig 3B show the results of the mixed effects of dietary components from various dietary indices on the risk of kidney stone within the WQS model. WQS regression results indicated that the mixed effects of the four dietary indices were negatively correlated with kidney stones, with the highest weight attributed to HEI2020 (49.2%), followed by DASH (26.4%), MED (21.8%), and AHEI (2.9%).

Fig 3 — (A) Spearman correlations among the MED, DASH, AHEI, and HEI-2020. (B) Mixed effects of the four dietary indices on kidney stone assessed by WQS. (C) Univariate exposure–response function and 95% CI scores for the associations between single dietary indices exposures when other dietary indices exposures are fixed at the median level. (D) Summary of the overall health effects of the combined exposures on the four dietary indices at various quantiles (from 25th to 75th) by BKMR. (E) Single-variable effects of dietary indices at decreasing quartiles for the kidney stone.

3.5 BKMR model to assess the effect of dietary index on kidney stones

We used the BKMR model, which is a nonparametric Bayesian variable selection framework to assess the combined effect of multiple dietary indices on kidney stones. We initially assessed the univariate exposure-response associations between single dietary index and kidney stones. Fig 3C illustrates a negative exposure-response trend for each dietary indices to the risk of kidney stones across the total population. The overall effect of the BKMR mixture assessment indicated that dietary indices levels at the 60th percentile and above were associated with significantly lower rates of kidney stones than exposure levels fixed at the 50th percentile (Fig 3D). Additionally, Fig 3E illustrates the single-variable effects of various dietary indices on the risk of kidney stones at the 25th, 50th, and 75th quantiles. HEI2020, DASH, MED, and AHEI are negative related with kidney stones at all three quantiles, indicating that higher levels of these dietary indices are correlated with a decreased risk of kidney stones.

The bivariate relationship was further explored by examining four dietary indices. Fig 4 presents the relationship between expos1 and the quantiles of expos2 for various dietary indices scores (HEI2020, DASH, MED, and AHEI). It shows the relationship between dietary indices in the column and kidney stones when the dietary index mixture in the row is fixed at its 25th, 50th, and 75th percentiles and the remaining dietary indices are fixed at its 50th percentile. There was a clear interaction between these dietary indices.

3.6 Intermediation effect analysis

As shown in the weighted multivariable linear regression models (Table 3), higher scores on all four healthy dietary indices were significantly associated with lower serum uric acid concentrations (all P < 0.05), with the inverse associations for MED and HEI-2020 being the most pronounced. These findings support the role of uric acid as a potential mediator in the relationship between dietary patterns and kidney stones. Further mediation analysis (Fig 5) indicated that uric acid was closely associated with all four dietary indices and acted as a mediator in their relationships with kidney stones. The mediating proportions of AHEI, DASH, HEI2020 and MED were 12.14%, 5.88%, 2.52% and 25.56%, respectively. The P value of mediating effect of DASH was 0.062, and the rest were less than 0.05, indicating that healthy diet had a great impact on the risk of kidney stones, and there was a mediating effect mediated by uric acid.

Table 3. The linear regression results of four dietary indices and uric acid.

Dietary indices	β(95%CI)	t	P
MED	−1.5241(−2.644, −0.405)	−2.668	0.010
HEI2020	−1.179 (−1.882, −0.476)	−3.287	0.001
AHEI	−0.251(−0.375, −0.127)	−3.962	< 0.001
DASH	−0.824(−1.182, −0.467)	−4.517	< 0.001

Open in a new tab

Linear regression models were adjusted for age, gender, race, education, BMI, cotinine, hypertension, and diabetes. MED, Mediterranean Diet; HEI2020, Healthy Eating Index-2020; AHEI, Alternate Healthy Eating Index; DASH, Dietary Approaches to Stop Hypertension.

Fig 5 — (A) Partial mediating effect of uric acid on the association between AHEI and the risk of kidney stone. (B) DASH and kidney stone. (C) HEI2020 and kidney stone. (D) MED and kidney stone. DE: Direct effect; IE: Indirect effect.

4. Discussion

This study investigated the association between the four dietary indices and the risk of kidney stones and the mediating role of uric acid levels in the relationship between diet and kidney stones. By analyzing the data from the NHANES database, we found that the OR for kidney stones decreased significantly with increasing AHEI, DASH, HEI2020, MED. This negative relationship remained robust after adjusting for potential confounders such as age, sex, race, Poverty Income Ratio (PIR), education level, marriage, BMI, smoking, alcohol consumption, Diabetes Mellitus (DM), and hypertension. Specifically, AHEI and DASH were inversely associated with the risk of kidney stones only above 31.75 and 21.96, while HEI2020 and MED were inversely associated with the risk of kidney stones. In addition, blood uric acid levels mediated the four dietary indices and the risk of kidney stones.

Multiple analyses were performed for the separate effects of the four dietary indices on the risk of kidney stones. Logistic regression analysis showed that MED showed a lower OR value in Crude model, Model 1 and Model 2. A stepwise modeling approach was used to demonstrate the stability of associations. The persistence of significant effects across Crude, Model 1, and Model 2 suggests that the observed relationships were not driven solely by demographic or clinical confounding. Correlation analysis showed that there was a high correlation among the four dietary indices, and the WQS regression model could be used to explore the total effect of mixed exposure and the relative contribution of each factor. WQS weight showed that HEI2020 had the highest proportion weight of 0.492, that is, HEI2020 had the greatest impact on the risk of kidney stones. In the BKMR forest plot, HEI2020 indicated a lower risk of kidney stones when quartile detection of the index was performed. In conclusion, in separate effect analyses, the MED and HEI2020 indexes had the greatest impact on kidney stone risk.

The AHEI advocates the consumption of fruits, vegetables, grains, and vegetable oils, while discouraging the consumption of sugar-sweetened beverages, alcohol, and meat [24]. AHEI was found to be significantly associated with gallstone risk reduction in previous studies [25], furthermore, the AHEI index has been proven to cause kidney stones through biological aging [26]. In the present study, we found that AHEI diet can inhibit the occurrence of kidney stones when it exceeds 31.75.

The DASH diet has been associated with a reduction in kidney stones in previous studies [27]. The DASH diet is associated with decreased calcium oxalate supersaturation, increased magnesium and citrate excretion, and increased urine pH [28]. Higher DASH score was associated with higher urine potassium, magnesium, phosphate, and pH, and lower relative supersaturations (RSS) of calcium oxalate (women only) and uric acid [29]. The DASH diet reduced the incidence of stones by changing the characteristics of urine [30]. The DASH diet is characterized by a high intake of fruits, vegetables, whole grains, and low-fat dairy products, as well as a low intake of sodium, red and processed meats, and added sugars. The DASH recommends a reduction in sodium intake while emphasizing dairy intake to promote kidney health and is related to the intake of calcium and phosphorus [31]. The DASH diet, which restricts the intake of meat protein, may reduce stone formation to a large extent through the mediating effect of uric acid.

HEI2020 encourages high intake of vegetables, fruits, and low-fat dairy products, which help to reduce uric acid levels and increase urine pH. Limiting refined grains and foods with a high oxalate content may reduce the risk of calcium oxalate stones. Emphasizing a balanced intake of calcium and magnesium in the diet can help reduce the likelihood of stone formation. Diet may influence stone risk by affecting the gut microbiota and altering oxalate metabolism and absorption [32,33]. This is consistent with the inhibition of stone formation by HEI2020 in this study.

The MED Mediterranean diet is rich in potassium, magnesium, and low in saturated fat, components that help to increase urine pH and reduce urinary calcium excretion, thereby reducing the risk of calcium oxalate and urate stones. A high-potassium dietary pattern is associated with a reduced risk of kidney stones, and fruits and vegetables in the Mediterranean diet are the main sources of potassium [34,35]. Kidney stone formation may be associated with chronic inflammation and oxidative stress, and the antioxidant components such as polyphenols and anti-inflammatory mechanisms of the Mediterranean diet help reduce these risks [36].

Because the healthy eating index was generally consistent in terms of dietary types, there was a high correlation and interaction among the four diets in this study, and the combined effect of multiple healthy eating indexes was significantly higher in reducing the risk of kidney stones. The diversity of healthy dietary patterns may optimize the urinary metabolic environment through the combined intake of potassium, magnesium, calcium, and antioxidant components. Reducing urinary calcium excretion (e.g., DASH), regulating urine pH (e.g., MED), and lowering uric acid levels (e.g., AHEI) may reduce stone risk through a combination of different pathways [37,38]. A study based on the NHS in the United States showed that the DASH and MED diets reduced the incidence of kidney stones, respectively, and this protective effect may be achieved by regulating urinary metabolic components and reducing inflammation [39]. In addition, this study identified lower uric acid levels as a mediator between multiple healthy dietary states and the risk of kidney stones. Uric acid level is an important cause of renal uric acid stones and other types of stones [40] which is affected by healthy diet level [41]. The AHEI diet emphasizes reducing the consumption of sugar-sweetened beverages, a feature that is particularly important for controlling uric acid levels [42]. The DASH diet was associated with most metabolic parameters, negatively correlated with triglycerides, urinary sodium, and uric acid, and positively correlated with serum vitamin D [43, 44]. Olive oil and nuts of the MED diet are rich in polyphenolic antioxidants, which reduce uric acid production and related tissue damage by inhibiting inflammation and oxidative stress. Both DASH and MED diets contribute to weight management, improve insulin resistance, and indirectly reduce uric acid levels [45,46].

Despite the significant findings of this study, several limitations should be acknowledged. First, the cross-sectional nature of the analysis precludes establishing causal relationships. Future longitudinal studies are essential to confirm the observed associations and mediation effects. Second, dietary data were based on 24-hour recall interviews, which may introduce recall bias and fail to capture long-term dietary habits accurately. Third, although uric acid’s mediating role was identified, the precise molecular mechanisms underlying this mediation remain unexplored and warrant further biological investigation. Fourth, while extensive covariate adjustments were performed, residual confounding due to unmeasured or unknown factors cannot be entirely ruled out. The strengths of this study include the use of a large, nationally representative sample with standardized dietary and biochemical assessments, the simultaneous evaluation of four major dietary indices, and the application of advanced analytical models (WQS and BKMR). From a public health perspective, these findings highlight that promoting healthy dietary patterns may help reduce kidney stone risk, partly through the regulation of uric acid metabolism. Moreover, artificial intelligence–driven dietary applications may offer innovative tools for personalized dietary monitoring and guidance, further supporting kidney stone prevention through improved nutritional balance.

5. Conclusion

In conclusion, this study provides robust evidence linking healthy dietary patterns to reduced kidney stone risk. Four dietary indices, including MED, DASH, AHEI, and HEI-2020, were negatively associated with kidney stone prevalence. MED and HEI-2020 had the strongest protective effects. Mediation analysis confirmed that uric acid partially mediates these associations, with MED showing the highest mediation proportion. These findings highlight the critical role of diet in kidney stone prevention and the potential mechanisms involving uric acid regulation.

Supporting information

S1 Table. Distribution of dietary indices for NHANES 2007–2018 (n = 25421).

(DOCX)

pone.0339839.s001.docx^{(17.6KB, docx)}

S1 Checklist. STROBE checklist v4 combined.

(DOCX)

pone.0339839.s002.docx^{(33.7KB, docx)}

Data Availability

All relevant data are within the manuscript and its Supporting Information files.

Funding Statement

This work was supported by the Natural Science Basic Research Program of Shaanxi Province (Grant No. 2020JQ-544), and the National Science Foundation for Young Scientists of China (Grant No. 82100812).

References

1.Abufaraj M, Xu T, Cao C, Waldhoer T, Seitz C, D’andrea D, et al. Prevalence and Trends in Kidney Stone Among Adults in the USA: Analyses of National Health and Nutrition Examination Survey 2007-2018 Data. Eur Urol Focus. 2021;7(6):1468–75. doi: 10.1016/j.euf.2020.08.011 [DOI] [PubMed] [Google Scholar]
2.Peerapen P, Thongboonkerd V. Kidney Stone Prevention. Adv Nutr. 2023;14(3):555–69. doi: 10.1016/j.advnut.2023.03.002 [DOI] [PMC free article] [PubMed] [Google Scholar]
3.Chewcharat A, Curhan G. Trends in the prevalence of kidney stones in the United States from 2007 to 2016. Urolithiasis. 2021;49(1):27–39. doi: 10.1007/s00240-020-01210-w [DOI] [PubMed] [Google Scholar]
4.Romero V, Akpinar H, Assimos DG. Kidney stones: a global picture of prevalence, incidence, and associated risk factors. Rev Urol. 2010;12(2–3):e86-96. [PMC free article] [PubMed] [Google Scholar]
5.Alelign T, Petros B. Kidney stone disease: an update on current concepts. Adv Urol. 2018;2018:3068365. [DOI] [PMC free article] [PubMed] [Google Scholar]
6.Lee JA, Abramowitz MK, Kipperman N, Drzewiecki BA, Melamed ML, Stern JM. Exploring the Association of Asthma with Urinary Stone Disease: Results from the National Health and Nutrition Examination Survey 2007-2014. Eur Urol Focus. 2020;6(2):354–60. doi: 10.1016/j.euf.2018.07.035 [DOI] [PubMed] [Google Scholar]
7.Ticinesi A, Nouvenne A, Borghi L, Meschi T. Water and other fluids in nephrolithiasis: State of the art and future challenges. Crit Rev Food Sci Nutr. 2017;57(5):963–74. doi: 10.1080/10408398.2014.964355 [DOI] [PubMed] [Google Scholar]
8.Abate V, Vergatti A, Iaccarino Idelson P, Recano C, Brancaccio M, Prezioso D, et al. Adherence to Mediterranean Diet, Dietary Salt Intake, and Susceptibility to Nephrolithiasis: A Case-Control Study. Nutrients. 2024;16(6):783. doi: 10.3390/nu16060783 [DOI] [PMC free article] [PubMed] [Google Scholar]
9.Littlejohns TJ, Neal NL, Bradbury KE, Heers H, Allen NE, Turney BW. Fluid Intake and Dietary Factors and the Risk of Incident Kidney Stones in UK Biobank: A Population-based Prospective Cohort Study. Eur Urol Focus. 2020;6(4):752–61. doi: 10.1016/j.euf.2019.05.002 [DOI] [PubMed] [Google Scholar]
10.Zhang C, Qiu S, Bian H, Tian B, Wang H, Tu X, et al. Association between Dietary Inflammatory Index and kidney stones in US adults: data from the National Health and Nutrition Examination Survey (NHANES) 2007–2016. Public Health Nutrition. 2021;24(18):6113–21. [DOI] [PMC free article] [PubMed] [Google Scholar]
11.Maddahi NS, Fotros D, Sohouli MH, Mozaffari-Khosravi H, Khayyatzadeh SS. Higher dietary insulin index is directly associated with the odd of kidney stones. Sci Rep. 2024;14(1):28302. doi: 10.1038/s41598-024-79419-7 [DOI] [PMC free article] [PubMed] [Google Scholar]
12.Bai S, Zhang Y, Guo C, Liu Y, Zhang Q, Liu L, et al. Associations between dietary patterns and nephrolithiasis risk in a large Chinese cohort: is a balanced or plant-based diet better?. Food Funct. 2023;14(7):3220–9. doi: 10.1039/d2fo03993a [DOI] [PubMed] [Google Scholar]
13.Li J, Wu Z, Xin S, Xu Y, Wang F, Liu Y, et al. Body mass index mediates the association between four dietary indices and phenotypic age acceleration in adults: a cross-sectional study. Food Funct. 2024;15(15):7828–36. doi: 10.1039/d4fo01088d [DOI] [PubMed] [Google Scholar]
14.Ma G, Zhang S, Luo Y, Zhang C, Xu W, Wang L. The association between composite dietary antioxidant index and rheumatoid arthritis: evidence from NHANES 2001-2020. BMC Rheumatol. 2024;8(1):74. doi: 10.1186/s41927-024-00447-x [DOI] [PMC free article] [PubMed] [Google Scholar]
15.Normand M, Haymann J-P, Daudon M. Medical treatment of uric acid kidney stones. Can Urol Assoc J. 2024;18(11):E339–45. doi: 10.5489/cuaj.8774 [DOI] [PMC free article] [PubMed] [Google Scholar]
16.Chen S-Y, Wang L, Yang J-W, Wang K-Y, Li X-R, Yang L. Mediterranean diet adherence and risk of kidney stones: Insights from a population-based study. Medicine (Baltimore). 2025;104(38):e44653. doi: 10.1097/MD.0000000000044653 [DOI] [PMC free article] [PubMed] [Google Scholar]
17.Maddahi N, Aghamir SMK, Moddaresi SS, Mirzaei K, Alizadeh S, Yekaninejad MS. The association of Dietary Approaches to Stop Hypertension-style diet with urinary risk factors of kidney stones formation in men with nephrolithiasis. Clin Nutr ESPEN. 2020;39:173–9. doi: 10.1016/j.clnesp.2020.06.021 [DOI] [PubMed] [Google Scholar]
18.Zhan JJ, Hodge RA, Dunlop AL, Lee MM, Bui L, Liang D, et al. Dietaryindex: a user-friendly and versatile R package for standardizing dietary pattern analysis in epidemiological and clinical studies. Am J Clin Nutr. 2024;120(5):1165–74. doi: 10.1016/j.ajcnut.2024.08.021 [DOI] [PMC free article] [PubMed] [Google Scholar]
19.Bernert JT, Jacob P 3rd, Holiday DB, Benowitz NL, Sosnoff CS, Doig MV, et al. Interlaboratory comparability of serum cotinine measurements at smoker and nonsmoker concentration levels: a round-robin study. Nicotine Tob Res. 2009;11(12):1458–66. [DOI] [PMC free article] [PubMed] [Google Scholar]
20.Lei T, Li M, Zhu Z, Yang J, Hu Y, Hua L. Comprehensive evaluation of serum cotinine on human health: Novel evidence for the systemic toxicity of tobacco smoke in the US general population. Sci Total Environ. 2023;892:164443. doi: 10.1016/j.scitotenv.2023.164443 [DOI] [PubMed] [Google Scholar]
21.Hicks CW, Wang D, Matsushita K, Windham BG, Selvin E. Peripheral Neuropathy and All-Cause and Cardiovascular Mortality in U.S. Adults : A Prospective Cohort Study. Ann Intern Med. 2021;174(2):167–74. doi: 10.7326/M20-1340 [DOI] [PMC free article] [PubMed] [Google Scholar]
22.Keil AP, Buckley JP, O’Brien KM, Ferguson KK, Zhao S, White AJ. A Quantile-Based g-Computation Approach to Addressing the Effects of Exposure Mixtures. Environ Health Perspect. 2020;128(4):47004. doi: 10.1289/EHP5838 [DOI] [PMC free article] [PubMed]
23.Bobb JF, Valeri L, Claus Henn B, Christiani DC, Wright RO, Mazumdar M, et al. Bayesian kernel machine regression for estimating the health effects of multi-pollutant mixtures. Biostatistics. 2015;16(3):493–508. doi: 10.1093/biostatistics/kxu058 [DOI] [PMC free article] [PubMed] [Google Scholar]
24.Fung TT, Meyer HE, Willett WC, Feskanich D. Association between Diet Quality Scores and Risk of Hip Fracture in Postmenopausal Women and Men Aged 50 Years and Older. J Acad Nutr Diet. 2018;118(12):2269-2279.e4. doi: 10.1016/j.jand.2017.11.022 [DOI] [PMC free article] [PubMed] [Google Scholar]
25.Wirth J, Song M, Fung TT, Joshi AD, Tabung FK, Chan AT, et al. Diet-quality scores and the risk of symptomatic gallstone disease: a prospective cohort study of male US health professionals. Int J Epidemiol. 2018;47(6):1938–46. doi: 10.1093/ije/dyy210 [DOI] [PMC free article] [PubMed] [Google Scholar]
26.Wei C, Yang Q, He J, Luo Y, Han K, Li J, et al. Healthy dietary patterns, biological aging, and kidney stones: evidence from NHANES 2007-2018. Front Nutr. 2025;12:1538289. doi: 10.3389/fnut.2025.1538289 [DOI] [PMC free article] [PubMed] [Google Scholar]
27.Taylor EN, Fung TT, Curhan GC. DASH-style diet associates with reduced risk for kidney stones. J Am Soc Nephrol. 2009;20(10):2253–9. doi: 10.1681/ASN.2009030276 [DOI] [PMC free article] [PubMed] [Google Scholar]
28.Noori N, Honarkar E, Goldfarb DS, Kalantar-Zadeh K, Taheri M, Shakhssalim N, et al. Urinary lithogenic risk profile in recurrent stone formers with hyperoxaluria: a randomized controlled trial comparing DASH (Dietary Approaches to Stop Hypertension)-style and low-oxalate diets. Am J Kidney Dis. 2014;63(3):456–63. doi: 10.1053/j.ajkd.2013.11.022 [DOI] [PubMed] [Google Scholar]
29.Taylor EN, Stampfer MJ, Mount DB, Curhan GC. DASH-style diet and 24-hour urine composition. Clin J Am Soc Nephrol. 2010;5(12):2315–22. doi: 10.2215/CJN.04420510 [DOI] [PMC free article] [PubMed] [Google Scholar]
30.Rodrigues FG, Lima TM, Zambrano L, Heilberg IP. Dietary pattern analysis among stone formers: resemblance to a DASH-style diet. J Bras Nefrol. 2020;42(3):338–48. doi: 10.1590/2175-8239-JBN-2019-0183 [DOI] [PMC free article] [PubMed] [Google Scholar]
31.Cena H, Calder PC. Defining a Healthy Diet: Evidence for The Role of Contemporary Dietary Patterns in Health and Disease. Nutrients. 2020;12(2). [DOI] [PMC free article] [PubMed] [Google Scholar]
32.Batagello CA, Monga M, Miller AW. Calcium oxalate urolithiasis: a case of missing microbes?. J Endourol. 2018;32(11):995–1005. [DOI] [PubMed] [Google Scholar]
33.Crivelli JJ, Mitchell T, Knight J, Wood KD, Assimos DG, Holmes RP, et al. Contribution of Dietary Oxalate and Oxalate Precursors to Urinary Oxalate Excretion. Nutrients. 2020;13(1). [DOI] [PMC free article] [PubMed] [Google Scholar]
34.Sorensen MD, Kahn AJ, Reiner AP, Tseng TY, Shikany JM, Wallace RB, et al. Impact of nutritional factors on incident kidney stone formation: a report from the WHI OS. J Urol. 2012;187(5):1645–9. doi: 10.1016/j.juro.2011.12.077 [DOI] [PMC free article] [PubMed] [Google Scholar]
35.Weaver CM. Potassium and health. Adv Nutr. 2013;4(3):368S-77S. doi: 10.3945/an.112.003533 [DOI] [PMC free article] [PubMed] [Google Scholar]
36.Çıtar Dazıroğlu ME, Acar Tek N. The Effect on Inflammation of Adherence to the Mediterranean Diet in Polycystic Ovary Syndrome. Curr Nutr Rep. 2023;12(1):191–202. doi: 10.1007/s13668-023-00451-6 [DOI] [PubMed] [Google Scholar]
37.Ferraro PM, Bargagli M, Trinchieri A, Gambaro G. Risk of kidney stones: influence of dietary factors, dietary patterns, and vegetarian-vegan diets. Nutrients. 2020;12(3). [DOI] [PMC free article] [PubMed] [Google Scholar]
38.Wang Y, Liu S, Zhao Q, Wang N, Liu X, Zhang T. Analysis of dietary patterns associated with kidney stone disease based on data-driven approaches: a case-control study in Shanghai. Nutrients. 2024;16(2). [DOI] [PMC free article] [PubMed] [Google Scholar]
39.Littlejohns TJ, Neal NL, Bradbury KE, Heers H, Allen NE, Turney BW. Fluid Intake and Dietary Factors and the Risk of Incident Kidney Stones in UK Biobank: A Population-based Prospective Cohort Study. Eur Urol Focus. 2020;6(4):752–61. doi: 10.1016/j.euf.2019.05.002 [DOI] [PubMed] [Google Scholar]
40.Ferraro PM, Curhan GC. Serum Uric Acid and Risk of Kidney Stones. Am J Kidney Dis. 2017;70(2):158–9. doi: 10.1053/j.ajkd.2017.05.004 [DOI] [PubMed] [Google Scholar]
41.Cheng S, Shan L, You Z, Xia Y, Zhao Y, Zhang H, et al. Dietary patterns, uric acid levels, and hyperuricemia: a systematic review and meta-analysis. Food Funct. 2023;14(17):7853–68. doi: 10.1039/d3fo02004e [DOI] [PubMed] [Google Scholar]
42.Choi HK, Curhan G. Soft drinks, fructose consumption, and the risk of gout in men: prospective cohort study. BMJ. 2008;336(7639):309–12. doi: 10.1136/bmj.39449.819271.BE [DOI] [PMC free article] [PubMed] [Google Scholar]
43.Vahid F, Hoge A, Hébert JR, Bohn T, ORISCAV working group*. Association of diet quality indices with serum and metabolic biomarkers in participants of the ORISCAV-LUX-2 study. Eur J Nutr. 2023;62(5):2063–85. doi: 10.1007/s00394-023-03095-y [DOI] [PMC free article] [PubMed]
44.Heindel J, Baid-Agrawal S, Rebholz CM, Nadal J, Schmid M, Schaeffner E, et al. Association Between Dietary Patterns and Kidney Function in Patients With Chronic Kidney Disease: A Cross-Sectional Analysis of the German Chronic Kidney Disease Study. J Ren Nutr. 2020;30(4):296–304. doi: 10.1053/j.jrn.2019.09.008 [DOI] [PMC free article] [PubMed]
45.Juraschek SP, Gelber AC, Choi HK, Appel LJ, Miller ER 3rd. Effects of the Dietary Approaches to Stop Hypertension (DASH) Diet and Sodium Intake on Serum Uric Acid. Arthritis Rheumatol. 2016;68(12):3002–9. [DOI] [PMC free article] [PubMed]
46.Angelico F, Baratta F, Coronati M, Ferro D, Del Ben M. Diet and metabolic syndrome: a narrative review. Intern Emerg Med. 2023;18(4):1007–17. doi: 10.1007/s11739-023-03226-7 [DOI] [PubMed] [Google Scholar]

PLoS One. doi: 10.1371/journal.pone.0339839.r001

Decision Letter 0

Yogesh Jain

15 Sep 2025

-->PONE-D-25-41276-->-->Uric acid levels mediate the association between four dietary indices and kidney stones in US adults: a cross-sectional study of NHANES 2007-2018-->-->PLOS ONE

Dear Dr. cao,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

==============================

Dear Authors,

The manuscript has received an overall positive feedback from all the designated reviewers, however, many suggestions have been received to refine the clarity of the derived messages as well as to establish the validity of the inferences. Kindly go through the comments provided below and refine accordingly for further consideration.

==============================

Please submit your revised manuscript by Oct 30 2025 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org . When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:-->

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols . Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols .

We look forward to receiving your revised manuscript.

Kind regards,

Yogesh Kumar Jain, MPH

Academic Editor

PLOS ONE

Journal Requirements:

When submitting your revision, we need you to address these additional requirements.

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at

https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and

https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf

2. Please include your tables as part of your main manuscript and remove the individual files. Please note that supplementary tables (should remain/ be uploaded) as separate "supporting information" files.

3. We noticed you have some minor occurrence of overlapping text with the following previous publication(s), which needs to be addressed:

https://www.researchgate.net/publication/260294589_Urinary_Lithogenic_Risk_Profile_in_Recurrent_Stone_Formers_With_Hyperoxaluria_A_Randomized_Controlled_Trial_Comparing_DASH_Dietary_Approaches_to_Stop_Hypertension-Style_and_Low-Oxalate_Diets?

https://www.mdpi.com/2072-6643/16/14/2248?

In your revision ensure you cite all your sources (including your own works), and quote or rephrase any duplicated text outside the methods section. Further consideration is dependent on these concerns being addressed.

4. Thank you for stating in your Funding Statement:

“This work was supported by the Natural Science Basic Research Program of Shaanxi Province (Grant No. 2020JQ-544), and the National Science Foundation for Young Scientists of China (Grant No. 82100812).”

Please provide an amended statement that declares *all* the funding or sources of support (whether external or internal to your organization) received during this study, as detailed online in our guide for authors at http://journals.plos.org/plosone/s/submit-now. Please also include the statement “There was no additional external funding received for this study.” in your updated Funding Statement.

Please include your amended Funding Statement within your cover letter. We will change the online submission form on your behalf.

5. Thank you for stating the following financial disclosure:

Please state what role the funders took in the study. If the funders had no role, please state: "The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript."

If this statement is not correct you must amend it as needed.

Please include this amended Role of Funder statement in your cover letter; we will change the online submission form on your behalf.

6. PLOS requires an ORCID iD for the corresponding author in Editorial Manager on papers submitted after December 6th, 2016. Please ensure that you have an ORCID iD and that it is validated in Editorial Manager. To do this, go to ‘Update my Information’ (in the upper left-hand corner of the main menu), and click on the Fetch/Validate link next to the ORCID field. This will take you to the ORCID site and allow you to create a new iD or authenticate a pre-existing iD in Editorial Manager.

7. If the reviewer comments include a recommendation to cite specific previously published works, please review and evaluate these publications to determine whether they are relevant and should be cited. There is no requirement to cite these works unless the editor has indicated otherwise.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

-->Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. -->

Reviewer #1: Partly

Reviewer #2: Yes

Reviewer #3: Yes

**********

-->2. Has the statistical analysis been performed appropriately and rigorously? -->

Reviewer #1: N/A

Reviewer #2: Yes

Reviewer #3: No

**********

-->3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.-->

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

**********

-->4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.-->

Reviewer #1: No

Reviewer #2: Yes

Reviewer #3: Yes

**********

-->5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)-->

Reviewer #1: Content-related Issues

1.Consider removing abbreviations that appear only once throughout the manuscript and using the full terms instead, to enhance readability.

2.Please report the observational study results following the STROBE checklist and provide the STROBE checklist in the supplementary materials.

3.The Introduction is insufficiently focused. Excessive space is devoted to describing other dietary indices, while the four dietary indices used in this study are underrepresented. This may impede reader comprehension.

4.In the Introduction, the sentence “This indicates that the animal-based diets may mediate the occurrence of kidney stones by influencing uric acid levels” appears abrupt. The preceding text does not clarify the relationship between animal-based diets and oxalate or calcium salts. Moreover, oxalate and calcium salts differ, as oxalate are primarily found in plants, not in animal-based diets.

5.Although the Introduction briefly mentions the association between uric acid and kidney stone formation, the link between dietary factors and uric acid is not addressed. Therefore, it is difficult to justify the hypothesis that uric acid mediates the relationship between dietary factors and kidney stones.

6.The statement “To our knowledge, few studies have investigated the relationship between healthy dietary indies” seems insufficiently supported. A search conducted in PubMed reveals multiple related studies, some using one of the four dietary indices, the NHANES database, or cohort study designs providing more robust evidence. The Introduction does not clearly highlight the novelty of this study, which may lead readers to question its significance. Please substantiate the rationale with adequate literature, clarify the research gap, and indicate the study’s innovation. (Note: indies is a spelling error; correct to indices.)

7. In the Methods section, the description in 2.1 Study Population and Design conflicts with the numbers and content shown in Figure 1. Please verify carefully.

8. Regarding kidney stone history in the Methods, is self-reported history sufficient to define kidney stones? How is potential bias addressed? Is there supporting evidence from high-quality literature?

9. In the Results section, based on the baseline characteristics table, the following conclusions may not be directly supported. Please reconsider and reference prior studies to accurately describe the study population:

“The smoking index cotinine indicates that smoking promotes the occurrence of kidney stones. In addition, education level and marital status also had a certain impact on kidney stones.”

10.Before conducting mediation analysis in the Results section, please consider presenting the relationship between the four dietary indices and uric acid, to justify uric acid as a potential mediator.

11.The sentence “Among them, MED restricted the intake of fat and protein more strictly, and the mediating effect of uric acid was more prominent” provides a speculative explanation and is not appropriate for the Results section. Consider moving it to the Discussion or removing it.

12.In the Discussion, the statement “However, no study has explored the relationship between AHEI and kidney stones” may be misleading. To my knowledge, prior studies have investigated the association between AHEI and kidney stones. Please review the literature carefully.

13.Please discuss the strengths of this study and its public health significance in the Discussion.

14.The figure legends lack essential information, such as covariates adjusted in the models and explanations of abbreviations in the figures. This may affect reader comprehension. Please provide the missing details.

Formatting-related Issues

15.The use of spacing throughout the manuscript is inconsistent. Please check carefully to maintain uniform formatting.

16.The references contain multiple inconsistencies in title capitalization and journal abbreviations. Please carefully review and correct these issues.

Reviewer #2: Notes

1. Did the authors check the normality of the data?

2. Can dietary apps based on artificial intelligence help reduce the risk of kidney stones? Adding this discussion point can be helpful in managing individual diets.

Reviewer #3: The study is actually interecting but it is need some revision as:

1. please explain the reason authors needs to divide the model into crude, 1 and 2

2. in the table 1 It would be more presentable if the author put age range

3. in the table 1 it would be more presentable if the author put BMI range

4. Please provides high-quality in every figures

**********

-->6. PLOS authors have the option to publish the peer review history of their article (what does this mean? ). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy .-->

Reviewer #1: No

Reviewer #2: No

Reviewer #3: Yes: Besut Daryanto

**********

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/ . PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org . Please note that Supporting Information files do not need this step.

Attachment

Submitted filename: PONE-D-25-41276_reviewer.docx

pone.0339839.s003.docx^{(318.8KB, docx)}

PLoS One. 2026 Jan 2;21(1):e0339839. doi: 10.1371/journal.pone.0339839.r002

Author response to Decision Letter 1

15 Oct 2025

Dear Editors and Reviewers:

Thank you for your letter and for the reviewers’ comments concerning our manuscript entitled “Uric acid levels mediate the association between four dietary indices and kidney stones in US adults: a cross-sectional study of NHANES 2007-2018” (ID: PONE-D-25-41276). Those comments are all valuable and very helpful for revising and improving our manuscript, as well as the important guiding significance to our researches. We have studied comments carefully and have made correction which we hope meet with approval. Revised portion are marked in red in the paper. The main corrections in the paper and the responds to the reviewer’s comments are as flowing:

Responds to the reviewer’s comments:

Reviewer #1:

Comment 1: Consider removing abbreviations that appear only once throughout the manuscript and using the full terms instead, to enhance readability.

Response: We appreciate the reviewer’s valuable suggestion. Following your advice, abbreviations that appeared only once have been replaced with their full terms to improve clarity and readability. Specifically, “USDA” was replaced with “United States Department of Agriculture.” In addition, the following abbreviations were defined at their first appearance in the text to ensure consistency: Poverty Income Ratio (PIR), Diabetes Mellitus (DM), and Body Mass Index (BMI). These revisions have been incorporated throughout the manuscript.

Comment 2: Please report the observational study results following the STROBE checklist and provide the STROBE checklist in the supplementary materials.

Response: We thank the reviewer for this important suggestion. In accordance with the recommendation, we have carefully reviewed our manuscript to ensure compliance with the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) guidelines. A completed STROBE checklist has been prepared and included in the supplementary materials to enhance the transparency and reporting quality of our study.

Comment 3: The Introduction is insufficiently focused. Excessive space is devoted to describing other dietary indices, while the four dietary indices used in this study are underrepresented. This may impede reader comprehension.

Response: We appreciate the reviewer’s comment. The Introduction has been revised to focus more specifically on the four dietary indices analyzed in this study (MED, HEI-2020, AHEI, and DASH). Descriptions of unrelated indices (e.g., DII, DIL) were shortened, and additional details on the components and relevance of the four indices have been added to improve clarity and reader comprehension.

Comment 4: In the Introduction, the sentence “This indicates that the animal-based diets may mediate the occurrence of kidney stones by influencing uric acid levels” appears abrupt. The preceding text does not clarify the relationship between animal-based diets and oxalate or calcium salts. Moreover, oxalate and calcium salts differ, as oxalate are primarily found in plants, not in animal-based diets.

Response: We agree and have revised the paragraph to clarify the biochemical relationships between diet, uric acid, and stone composition. The new text explains that animal-based protein intake increases uric acid production, whereas oxalate is mainly derived from plant-based foods, thereby resolving the logical inconsistency.

Comment 5: Although the Introduction briefly mentions the association between uric acid and kidney stone formation, the link between dietary factors and uric acid is not addressed. Therefore, it is difficult to justify the hypothesis that uric acid mediates the relationship between dietary factors and kidney stones.

Response: Thank you for this suggestion. We added a paragraph describing how dietary components influence uric acid metabolism—highlighting the effects of purine-rich foods, fructose, alcohol, and plant-based diets—thus providing a clear rationale for investigating uric acid as a mediator.

Comment 6: The statement “To our knowledge, few studies have investigated the relationship between healthy dietary indies” seems insufficiently supported. A search conducted in PubMed reveals multiple related studies, some using one of the four dietary indices, the NHANES database, or cohort study designs providing more robust evidence. The Introduction does not clearly highlight the novelty of this study, which may lead readers to question its significance. Please substantiate the rationale with adequate literature, clarify the research gap, and indicate the study’s innovation. (Note: indies is a spelling error; correct to indices.)

Response: Thank you for this suggestion. We revised this statement to “Although several studies have examined individual dietary indices such as DASH or MED, few have comprehensively compared multiple healthy dietary indices while examining uric acid as a mediator.” We also emphasized the novelty of our integrative approach using NHANES data and clarified the research gap in the Introduction. The term “indies” was corrected to “indices.”

Comment 7: In the Methods section, the description in 2.1 Study Population and Design conflicts with the numbers and content shown in Figure 1. Please verify carefully.

Response: Thank you for identifying this inconsistency. We carefully re-checked the participant selection and confirm that the sample sizes reported in the analyses are correct. The discrepancy arose from a typographical error in the Methods text, which incorrectly stated exclusion of participants aged <20 years. We have corrected the Methods section so that it now consistently states exclusion of participants <18 years to match Figure 1. No participant counts, analytic procedures, or results were changed. We apologize for the oversight and appreciate the reviewer’s careful reading.

Comment 8: Regarding kidney stone history in the Methods, is self-reported history sufficient to define kidney stones? How is potential bias addressed? Is there supporting evidence from high-quality literature?

Response: We thank the reviewer for this valuable comment. We acknowledge that self-reported kidney stone history may be subject to potential misclassification bias. However, in large-scale epidemiological surveys such as NHANES, clinical verification for all participants is not feasible. The use of a self-reported, physician-diagnosed history collected via standardized questionnaires administered by trained interviewers is the established and widely accepted approach in this field. This standardized procedure minimizes variability.

We reviewed a large number of analyses by others on the data of NHENES kidney stones, but none of them had a process for dealing with this bias. The main references are as follows:

[1]. Chen Y, Zhang J, Li Z, Zhan Y, Tang Z, Wang J, He Z, Tang F. Causal relationship between basal metabolic rate and kidney stone disease: from discovery in US NHANES to evidence in UK Biobank cohorts. Int J Surg. 2025 Sep 1;111(9):6063-6074. doi: 10.1097/JS9.0000000000002658.

[2]. Zhou Y, Li X, He Q, Feng Q, Liu Y, Liao B. The advanced lung cancer inflammation index as a predictor of kidney stone risk in men: a cross-sectional analysis. Front Nutr. 2025 Jul 24;12:1568427. doi: 10.3389/fnut.2025.1568427.

[3]. Wei C, Yang Q, He J, Luo Y, Han K, Li J, Su S, Zhang J, Wang H, Wang D. Healthy dietary patterns, biological aging, and kidney stones: evidence from NHANES 2007-2018. Front Nutr. 2025 Mar 25;12:1538289. doi: 10.3389/fnut.2025.1538289.

Comment 9: In the Results section, based on the baseline characteristics table, the following conclusions may not be directly supported. Please reconsider and reference prior studies to accurately describe the study population:

“The smoking index cotinine indicates that smoking promotes the occurrence of kidney stones. In addition, education level and marital status also had a certain impact on kidney stones.”

Response: We thank the reviewer for this helpful observation. We agree that the original statements could be interpreted as implying causality, which is not appropriate for descriptive statistics. Accordingly, we have revised the text to present a neutral and data-driven description of the baseline characteristics. And the changes have been incorporated into the Results section of the revised manuscript. The revised statement now reads as follows: “Participants with kidney stones had higher serum cotinine levels, suggesting greater tobacco exposure, consistent with previous reports linking smoking to metabolic disturbances related to stone risk. Differences in education and marital status were also observed but require further investigation.”

Comment 10: Before conducting mediation analysis in the Results section, please consider presenting the relationship between the four dietary indices and uric acid, to justify uric acid as a potential mediator.

Response: We thank the reviewer for this valuable suggestion. In response, we added a supplementary analysis to examine the associations between each dietary index and serum uric acid levels. The results showed that higher MED, AHEI, HEI-2020, and DASH scores were significantly associated with lower uric acid concentrations (all P < 0.05), supporting the role of uric acid as a potential mediator. This new analysis has been added to the Results section and presented prior to the mediation models (Figure 5).

Comment 11: The sentence “Among them, MED restricted the intake of fat and protein more strictly, and the mediating effect of uric acid was more prominent” provides a speculative explanation and is not appropriate for the Results section. Consider moving it to the Discussion or removing it.

Response: We sincerely thank the reviewer for this valuable suggestion. We fully agree that this statement was speculative and not appropriate for inclusion in the Results section. Accordingly, we have removed this sentence from the revised manuscript to maintain the objectivity and accuracy of the Results presentation.

Comment 12: In the Discussion, the statement “However, no study has explored the relationship between AHEI and kidney stones” may be misleading. To my knowledge, prior studies have investigated the association between AHEI and kidney stones. Please review the literature carefully.

Response: We thank the reviewer for this insightful comment. Upon re-examining the literature, we found that a recent study has indeed investigated the association between the Alternate Healthy Eating Index (AHEI) and kidney stone risk. This reference was published after our initial analysis and drafting of the manuscript, which led to its unintentional omission. We have now revised the statement to accurately reflect the existing evidence and have cited the relevant study in the Discussion section.

Comment 13: Please discuss the strengths of this study and its public health significance in the Discussion.

Response: Thank you very much for this valuable suggestion. We only discussed the shortcomings and did not conduct a perfect discussion on the advantages. The shortcomings of the discussion were followed by highlighting the public health significance of this study.

“The strengths of this study include the use of a large, nationally representative sample with standardized dietary and biochemical assessments, the simultaneous evaluation of four dietary indices, and the application of advanced mixture models (WQS and BKMR). From a public health perspective, our findings emphasize that promoting healthy eating patterns could reduce kidney stone risk partly through uric acid regulation, supporting dietary modification as a cost-effective prevention strategy.”

Comment 14: The figure legends lack essential information, such as covariates adjusted in the models and explanations of abbreviations in the figures. This may affect reader comprehension. Please provide the missing details.

Response: We thank the reviewer for this helpful suggestion. We have revised all figure and table legends to make them more self-explanatory. Specifically, the legends now include details on the covariates adjusted in the regression models and full explanations of all abbreviations used. These modifications improve clarity and reader comprehension.

Formatting-related Issues

Comment 15: The use of spacing throughout the manuscript is inconsistent. Please check carefully to maintain uniform formatting.

Response: We appreciate this comment. The manuscript has been reformatted throughout using 12 font size and 22-point line spacing to ensure consistency and readability in accordance with journal formatting requirements.

Comment 16: The references contain multiple inconsistencies in title capitalization and journal abbreviations. Please carefully review and correct these issues.

Response: Thank you for pointing this out. We have thoroughly reviewed and standardized all references according to the journal’s formatting guidelines, ensuring consistency in title capitalization, punctuation, and journal name abbreviations.

Reviewer #2:

Comment 1: Did the authors check the normality of the data?

Response: Thank you for raising this important point regarding data normality. In this study, we employed an initial data quality check by examining the maximum and minimum values for all continuous variables to identify any potential outliers or data entry errors. No anomalous values were found that fell outside biologically or clinically plausible ranges, which we attribute to the rigorous data management and quality control procedures inherent to the NHANES database.

Comment 2: Can dietary apps based on artificial intelligence help reduce the risk of kidney stones? Adding this discussion point can be helpful in managing individual diets.

Response: We sincerely thank the reviewer for this insightful suggestion. We agree that artificial intelligence (AI)-based dietary applications hold great potential for improving personalized nutrition management. Such tools have been successfully applied in weight control, dietary assessment, and chronic disease prevention. By integrating AI algorithms to monitor total food intake, estimate nutrient composition, and evaluate dietary indices over time, these applications could help individuals maintain healthier eating patterns and potentially reduce the risk of kidney stones. Therefore, in the revised "Discussion" section, we added new content to the discussion, exploring the potential role that AI-driven diet apps can play in individualized prevention and management of kidney stones.

Reviewer #3: The study is actually interecting but it is needing some revision as:

Comment 1: please explain the reason authors needs to divide the model into crude, 1 and 2.

Response: Thank you for your insightful comment. We divided the logistic regression analysis into three models to assess the stability and independence of the associations between dietary indices and kidney stones. Specifically, the Crude model represents the unadjusted association; Model 1 adjusts for basic demographic factors (age, sex, and race); and Model 2 further adjusts for socioeconomic and clinical covariates (education level, marital status, BMI, cotinine, alcohol consumption, hypertension, and diabetes). This stepwise adjustment approach allows us to examine whether the observed associations persist after controlling for potential confounding factors and to better understand how each set of variables influences the relationship between dietary indices and kidney stone risk. We have clarified this explanation in the Methods section.

Comment 2: in the table 1 It would be more presentable if the author put age range.

Response: Thank you very much for this question. The age range (20–80 years) has now been clearly indicated in Table 1.

Comment 3: in the table 1 it would be more presentable if the author put BMI range.

Response: Thank you very much for this question. The BMI ranges have been added as follows: overall and non-stone group (13.18–84.40), and stone group (15.10–67.83). These values are now included in the revised Table 1.

Comment 4: Please provides high-quality in every figure.

Response: Thank you for your comments on the Figures. We have carefully checked the image quality, and there should be no ambiguity. The pixels of the 5 Figures in this study are all 300bpi, and

Attachment

Submitted filename: Response to Reviewers.docx

pone.0339839.s005.docx^{(25.9KB, docx)}

PLoS One. doi: 10.1371/journal.pone.0339839.r003

Decision Letter 1

Yogesh Jain

18 Nov 2025

<div>PONE-D-25-41276R1-->-->Uric acid levels mediate the association between four dietary indices and kidney stones in US adults: a cross-sectional study of NHANES 2007-2018-->-->PLOS ONE

Dear Dr. cao,

Dear Authors, the reviewers have again suggested some major revisions. I recommend you revise the manuscript carefully based on the comments for reconsideration by the referees and subsequent decision.

Please submit your revised manuscript by Jan 02 2026 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org . When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:-->

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

We look forward to receiving your revised manuscript.

Kind regards,

Yogesh Kumar Jain, PhD

Academic Editor

PLOS ONE

Journal Requirements:

If the reviewer comments include a recommendation to cite specific previously published works, please review and evaluate these publications to determine whether they are relevant and should be cited. There is no requirement to cite these works unless the editor has indicated otherwise.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

-->Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.-->

Reviewer #2: All comments have been addressed

Reviewer #3: All comments have been addressed

**********

-->2. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #2: Yes

Reviewer #3: Yes

**********

-->3. Has the statistical analysis been performed appropriately and rigorously? -->

Reviewer #2: Yes

Reviewer #3: No

**********

-->4. Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #2: Yes

Reviewer #3: Yes

**********

-->5. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #2: Yes

Reviewer #3: No

**********

-->6. Review Comments to the Author

Reviewer #2: (No Response)

Reviewer #3: Please provide different age groups and BMI group range (ex: age: 20-30, 30-40, 40-50,50-60,60-70 or < 50 and > 50 (and reason behind that) BMI: < 18.5, 18.5 - 24.9, 25 - 29.9, 30-39.9, and > 40), instead of only stating the range and mean number. Providing age groups (not only stating the overall age range), might help enhance the discussion since it affects the BMI and might affect the overall result of this study. Thus, necessary to be stated and discussed.

**********

-->7. PLOS authors have the option to publish the peer review history of their article (what does this mean? ). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy .-->

Reviewer #2: No

Reviewer #3: Yes: Besut Daryanto

**********

To ensure your figures meet our technical requirements, please review our figure guidelines: https://journals.plos.org/plosone/s/figures

You may also use PLOS’s free figure tool, NAAS, to help you prepare publication quality figures: https://journals.plos.org/plosone/s/figures#loc-tools-for-figure-preparation.

NAAS will assess whether your figures meet our technical requirements by comparing each figure against our figure specifications.

PLoS One. 2026 Jan 2;21(1):e0339839. doi: 10.1371/journal.pone.0339839.r004

Author response to Decision Letter 2

24 Nov 2025

Dear Editors and Reviewers:

Responds to the reviewer’s comments:

Reviewer #3:

Comment 1: Please provide different age groups and BMI group range (ex: age: 20-30, 30-40, 40-50,50-60,60-70 or < 50 and > 50 (and reason behind that) BMI: < 18.5, 18.5 - 24.9, 25 - 29.9, 30-39.9, and > 40), instead of only stating the range and mean number. Providing age groups (not only stating the overall age range), might help enhance the discussion since it affects the BMI and might affect the overall result of this study. Thus, necessary to be stated and discussed.

Response: Thank you very much for your valuable comment. We apologize for the misunderstanding in our previous revision. In the updated manuscript, we have revised the demographic data presentation according to your suggestion. Specifically, age has now been categorized into two groups (<60 years and ≥60 years) based on widely accepted WHO criteria for defining older adults, which may better reflect differences related to the elderly status. In addition, BMI has been regrouped following WHO standards into <18.5 (underweight), 18.5–25 (normal weight), 25–30 (overweight), and ≥30 (obesity). These subgroup classifications have been incorporated into both the Results and Discussion sections to better explore their potential influence on BMI-related outcomes and overall study findings.

In addition, the editor's summary of the reviewers' opinions and the overall evaluation of the article are also very helpful, and we have followed the suggestions to revise it one by one.

In all, I found the reviewer’ s comments and the editor's summary are quite helpful, and I revised my paper point-by-point. Thank you and the review again for your help! We tried our best to improve the manuscript and made some changes in the manuscript. These changes will not influence the content and framework of the paper. And here we did not list the changes but marked in red in revised paper.

We appreciate for Editors/Reviewer’ warm work earnestly, and hope that the revision will meet with approval. Once again, thank you very much for your comments and suggestions.

Attachment

Submitted filename: Response_to_Reviewers_auresp_2.docx

pone.0339839.s006.docx^{(17.8KB, docx)}

PLoS One. doi: 10.1371/journal.pone.0339839.r005

Decision Letter 2

Yogesh Jain

14 Dec 2025

Uric acid levels mediate the association between four dietary indices and kidney stones in US adults: a cross-sectional study of NHANES 2007-2018

PONE-D-25-41276R2

Dear Dr. cao,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

An invoice will be generated when your article is formally accepted. Please note, if your institution has a publishing partnership with PLOS and your article meets the relevant criteria, all or part of your publication costs will be covered. Please make sure your user information is up-to-date by logging into Editorial Manager at Editorial Manager® and clicking the ‘Update My Information' link at the top of the page. For questions related to billing, please contact billing support .

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Yogesh Kumar Jain, PhD

Academic Editor

PLOS One

Additional Editor Comments (optional):

Reviewers' comments:

Reviewer's Responses to Questions

-->Comments to the Author

Reviewer #2: All comments have been addressed

Reviewer #3: All comments have been addressed

**********

-->2. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #2: Yes

Reviewer #3: Yes

**********

-->3. Has the statistical analysis been performed appropriately and rigorously? -->

Reviewer #2: Yes

Reviewer #3: Yes

**********

-->4. Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #2: Yes

Reviewer #3: Yes

**********

-->5. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #2: Yes

Reviewer #3: Yes

**********

-->6. Review Comments to the Author

Reviewer #2: (No Response)

Reviewer #3: Dear author,

Actually overall the manuscript revised is good, but the author has not provided the high-quality figure yet.

Best regards,

**********

-->7. PLOS authors have the option to publish the peer review history of their article (what does this mean? ). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy .-->

Reviewer #2: No

Reviewer #3: Yes: Dr. dr. Besut Daryanto, Sp.B., Sp.U(K)

**********

PLoS One. doi: 10.1371/journal.pone.0339839.r006

Acceptance letter

Yogesh Jain

PONE-D-25-41276R2

PLOS One

Dear Dr. Cao,

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS One. Congratulations! Your manuscript is now being handed over to our production team.

At this stage, our production department will prepare your paper for publication. This includes ensuring the following:

* All references, tables, and figures are properly cited

* All relevant supporting information is included in the manuscript submission,

* There are no issues that prevent the paper from being properly typeset

You will receive further instructions from the production team, including instructions on how to review your proof when it is ready. Please keep in mind that we are working through a large volume of accepted articles, so please give us a few days to review your paper and let you know the next and final steps.

Lastly, if your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

You will receive an invoice from PLOS for your publication fee after your manuscript has reached the completed accept phase. If you receive an email requesting payment before acceptance or for any other service, this may be a phishing scheme. Learn how to identify phishing emails and protect your accounts at https://explore.plos.org/phishing.

If we can help with anything else, please email us at customercare@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Yogesh Kumar Jain

Academic Editor

PLOS One

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

S1 Table. Distribution of dietary indices for NHANES 2007–2018 (n = 25421).

(DOCX)

pone.0339839.s001.docx^{(17.6KB, docx)}

S1 Checklist. STROBE checklist v4 combined.

(DOCX)

pone.0339839.s002.docx^{(33.7KB, docx)}

Attachment

Submitted filename: PONE-D-25-41276_reviewer.docx

pone.0339839.s003.docx^{(318.8KB, docx)}

Attachment

Submitted filename: Response to Reviewers.docx

pone.0339839.s005.docx^{(25.9KB, docx)}

Attachment

Submitted filename: Response_to_Reviewers_auresp_2.docx

pone.0339839.s006.docx^{(17.8KB, docx)}

Data Availability Statement

All relevant data are within the manuscript and its Supporting Information files.

[pone.0339839.ref001] 1.Abufaraj M, Xu T, Cao C, Waldhoer T, Seitz C, D’andrea D, et al. Prevalence and Trends in Kidney Stone Among Adults in the USA: Analyses of National Health and Nutrition Examination Survey 2007-2018 Data. Eur Urol Focus. 2021;7(6):1468–75. doi: 10.1016/j.euf.2020.08.011 [DOI] [PubMed] [Google Scholar]

[pone.0339839.ref002] 2.Peerapen P, Thongboonkerd V. Kidney Stone Prevention. Adv Nutr. 2023;14(3):555–69. doi: 10.1016/j.advnut.2023.03.002 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0339839.ref003] 3.Chewcharat A, Curhan G. Trends in the prevalence of kidney stones in the United States from 2007 to 2016. Urolithiasis. 2021;49(1):27–39. doi: 10.1007/s00240-020-01210-w [DOI] [PubMed] [Google Scholar]

[pone.0339839.ref004] 4.Romero V, Akpinar H, Assimos DG. Kidney stones: a global picture of prevalence, incidence, and associated risk factors. Rev Urol. 2010;12(2–3):e86-96. [PMC free article] [PubMed] [Google Scholar]

[pone.0339839.ref005] 5.Alelign T, Petros B. Kidney stone disease: an update on current concepts. Adv Urol. 2018;2018:3068365. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0339839.ref006] 6.Lee JA, Abramowitz MK, Kipperman N, Drzewiecki BA, Melamed ML, Stern JM. Exploring the Association of Asthma with Urinary Stone Disease: Results from the National Health and Nutrition Examination Survey 2007-2014. Eur Urol Focus. 2020;6(2):354–60. doi: 10.1016/j.euf.2018.07.035 [DOI] [PubMed] [Google Scholar]

[pone.0339839.ref007] 7.Ticinesi A, Nouvenne A, Borghi L, Meschi T. Water and other fluids in nephrolithiasis: State of the art and future challenges. Crit Rev Food Sci Nutr. 2017;57(5):963–74. doi: 10.1080/10408398.2014.964355 [DOI] [PubMed] [Google Scholar]

[pone.0339839.ref008] 8.Abate V, Vergatti A, Iaccarino Idelson P, Recano C, Brancaccio M, Prezioso D, et al. Adherence to Mediterranean Diet, Dietary Salt Intake, and Susceptibility to Nephrolithiasis: A Case-Control Study. Nutrients. 2024;16(6):783. doi: 10.3390/nu16060783 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0339839.ref009] 9.Littlejohns TJ, Neal NL, Bradbury KE, Heers H, Allen NE, Turney BW. Fluid Intake and Dietary Factors and the Risk of Incident Kidney Stones in UK Biobank: A Population-based Prospective Cohort Study. Eur Urol Focus. 2020;6(4):752–61. doi: 10.1016/j.euf.2019.05.002 [DOI] [PubMed] [Google Scholar]

[pone.0339839.ref010] 10.Zhang C, Qiu S, Bian H, Tian B, Wang H, Tu X, et al. Association between Dietary Inflammatory Index and kidney stones in US adults: data from the National Health and Nutrition Examination Survey (NHANES) 2007–2016. Public Health Nutrition. 2021;24(18):6113–21. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0339839.ref011] 11.Maddahi NS, Fotros D, Sohouli MH, Mozaffari-Khosravi H, Khayyatzadeh SS. Higher dietary insulin index is directly associated with the odd of kidney stones. Sci Rep. 2024;14(1):28302. doi: 10.1038/s41598-024-79419-7 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0339839.ref012] 12.Bai S, Zhang Y, Guo C, Liu Y, Zhang Q, Liu L, et al. Associations between dietary patterns and nephrolithiasis risk in a large Chinese cohort: is a balanced or plant-based diet better?. Food Funct. 2023;14(7):3220–9. doi: 10.1039/d2fo03993a [DOI] [PubMed] [Google Scholar]

[pone.0339839.ref013] 13.Li J, Wu Z, Xin S, Xu Y, Wang F, Liu Y, et al. Body mass index mediates the association between four dietary indices and phenotypic age acceleration in adults: a cross-sectional study. Food Funct. 2024;15(15):7828–36. doi: 10.1039/d4fo01088d [DOI] [PubMed] [Google Scholar]

[pone.0339839.ref014] 14.Ma G, Zhang S, Luo Y, Zhang C, Xu W, Wang L. The association between composite dietary antioxidant index and rheumatoid arthritis: evidence from NHANES 2001-2020. BMC Rheumatol. 2024;8(1):74. doi: 10.1186/s41927-024-00447-x [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0339839.ref015] 15.Normand M, Haymann J-P, Daudon M. Medical treatment of uric acid kidney stones. Can Urol Assoc J. 2024;18(11):E339–45. doi: 10.5489/cuaj.8774 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0339839.ref016] 16.Chen S-Y, Wang L, Yang J-W, Wang K-Y, Li X-R, Yang L. Mediterranean diet adherence and risk of kidney stones: Insights from a population-based study. Medicine (Baltimore). 2025;104(38):e44653. doi: 10.1097/MD.0000000000044653 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0339839.ref017] 17.Maddahi N, Aghamir SMK, Moddaresi SS, Mirzaei K, Alizadeh S, Yekaninejad MS. The association of Dietary Approaches to Stop Hypertension-style diet with urinary risk factors of kidney stones formation in men with nephrolithiasis. Clin Nutr ESPEN. 2020;39:173–9. doi: 10.1016/j.clnesp.2020.06.021 [DOI] [PubMed] [Google Scholar]

[pone.0339839.ref018] 18.Zhan JJ, Hodge RA, Dunlop AL, Lee MM, Bui L, Liang D, et al. Dietaryindex: a user-friendly and versatile R package for standardizing dietary pattern analysis in epidemiological and clinical studies. Am J Clin Nutr. 2024;120(5):1165–74. doi: 10.1016/j.ajcnut.2024.08.021 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0339839.ref019] 19.Bernert JT, Jacob P 3rd, Holiday DB, Benowitz NL, Sosnoff CS, Doig MV, et al. Interlaboratory comparability of serum cotinine measurements at smoker and nonsmoker concentration levels: a round-robin study. Nicotine Tob Res. 2009;11(12):1458–66. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0339839.ref020] 20.Lei T, Li M, Zhu Z, Yang J, Hu Y, Hua L. Comprehensive evaluation of serum cotinine on human health: Novel evidence for the systemic toxicity of tobacco smoke in the US general population. Sci Total Environ. 2023;892:164443. doi: 10.1016/j.scitotenv.2023.164443 [DOI] [PubMed] [Google Scholar]

[pone.0339839.ref021] 21.Hicks CW, Wang D, Matsushita K, Windham BG, Selvin E. Peripheral Neuropathy and All-Cause and Cardiovascular Mortality in U.S. Adults : A Prospective Cohort Study. Ann Intern Med. 2021;174(2):167–74. doi: 10.7326/M20-1340 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0339839.ref022] 22.Keil AP, Buckley JP, O’Brien KM, Ferguson KK, Zhao S, White AJ. A Quantile-Based g-Computation Approach to Addressing the Effects of Exposure Mixtures. Environ Health Perspect. 2020;128(4):47004. doi: 10.1289/EHP5838 [DOI] [PMC free article] [PubMed]

[pone.0339839.ref023] 23.Bobb JF, Valeri L, Claus Henn B, Christiani DC, Wright RO, Mazumdar M, et al. Bayesian kernel machine regression for estimating the health effects of multi-pollutant mixtures. Biostatistics. 2015;16(3):493–508. doi: 10.1093/biostatistics/kxu058 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0339839.ref024] 24.Fung TT, Meyer HE, Willett WC, Feskanich D. Association between Diet Quality Scores and Risk of Hip Fracture in Postmenopausal Women and Men Aged 50 Years and Older. J Acad Nutr Diet. 2018;118(12):2269-2279.e4. doi: 10.1016/j.jand.2017.11.022 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0339839.ref025] 25.Wirth J, Song M, Fung TT, Joshi AD, Tabung FK, Chan AT, et al. Diet-quality scores and the risk of symptomatic gallstone disease: a prospective cohort study of male US health professionals. Int J Epidemiol. 2018;47(6):1938–46. doi: 10.1093/ije/dyy210 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0339839.ref026] 26.Wei C, Yang Q, He J, Luo Y, Han K, Li J, et al. Healthy dietary patterns, biological aging, and kidney stones: evidence from NHANES 2007-2018. Front Nutr. 2025;12:1538289. doi: 10.3389/fnut.2025.1538289 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0339839.ref027] 27.Taylor EN, Fung TT, Curhan GC. DASH-style diet associates with reduced risk for kidney stones. J Am Soc Nephrol. 2009;20(10):2253–9. doi: 10.1681/ASN.2009030276 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0339839.ref028] 28.Noori N, Honarkar E, Goldfarb DS, Kalantar-Zadeh K, Taheri M, Shakhssalim N, et al. Urinary lithogenic risk profile in recurrent stone formers with hyperoxaluria: a randomized controlled trial comparing DASH (Dietary Approaches to Stop Hypertension)-style and low-oxalate diets. Am J Kidney Dis. 2014;63(3):456–63. doi: 10.1053/j.ajkd.2013.11.022 [DOI] [PubMed] [Google Scholar]

[pone.0339839.ref029] 29.Taylor EN, Stampfer MJ, Mount DB, Curhan GC. DASH-style diet and 24-hour urine composition. Clin J Am Soc Nephrol. 2010;5(12):2315–22. doi: 10.2215/CJN.04420510 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0339839.ref030] 30.Rodrigues FG, Lima TM, Zambrano L, Heilberg IP. Dietary pattern analysis among stone formers: resemblance to a DASH-style diet. J Bras Nefrol. 2020;42(3):338–48. doi: 10.1590/2175-8239-JBN-2019-0183 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0339839.ref031] 31.Cena H, Calder PC. Defining a Healthy Diet: Evidence for The Role of Contemporary Dietary Patterns in Health and Disease. Nutrients. 2020;12(2). [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0339839.ref032] 32.Batagello CA, Monga M, Miller AW. Calcium oxalate urolithiasis: a case of missing microbes?. J Endourol. 2018;32(11):995–1005. [DOI] [PubMed] [Google Scholar]

[pone.0339839.ref033] 33.Crivelli JJ, Mitchell T, Knight J, Wood KD, Assimos DG, Holmes RP, et al. Contribution of Dietary Oxalate and Oxalate Precursors to Urinary Oxalate Excretion. Nutrients. 2020;13(1). [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0339839.ref034] 34.Sorensen MD, Kahn AJ, Reiner AP, Tseng TY, Shikany JM, Wallace RB, et al. Impact of nutritional factors on incident kidney stone formation: a report from the WHI OS. J Urol. 2012;187(5):1645–9. doi: 10.1016/j.juro.2011.12.077 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0339839.ref035] 35.Weaver CM. Potassium and health. Adv Nutr. 2013;4(3):368S-77S. doi: 10.3945/an.112.003533 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0339839.ref036] 36.Çıtar Dazıroğlu ME, Acar Tek N. The Effect on Inflammation of Adherence to the Mediterranean Diet in Polycystic Ovary Syndrome. Curr Nutr Rep. 2023;12(1):191–202. doi: 10.1007/s13668-023-00451-6 [DOI] [PubMed] [Google Scholar]

[pone.0339839.ref037] 37.Ferraro PM, Bargagli M, Trinchieri A, Gambaro G. Risk of kidney stones: influence of dietary factors, dietary patterns, and vegetarian-vegan diets. Nutrients. 2020;12(3). [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0339839.ref038] 38.Wang Y, Liu S, Zhao Q, Wang N, Liu X, Zhang T. Analysis of dietary patterns associated with kidney stone disease based on data-driven approaches: a case-control study in Shanghai. Nutrients. 2024;16(2). [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0339839.ref039] 39.Littlejohns TJ, Neal NL, Bradbury KE, Heers H, Allen NE, Turney BW. Fluid Intake and Dietary Factors and the Risk of Incident Kidney Stones in UK Biobank: A Population-based Prospective Cohort Study. Eur Urol Focus. 2020;6(4):752–61. doi: 10.1016/j.euf.2019.05.002 [DOI] [PubMed] [Google Scholar]

[pone.0339839.ref040] 40.Ferraro PM, Curhan GC. Serum Uric Acid and Risk of Kidney Stones. Am J Kidney Dis. 2017;70(2):158–9. doi: 10.1053/j.ajkd.2017.05.004 [DOI] [PubMed] [Google Scholar]

[pone.0339839.ref041] 41.Cheng S, Shan L, You Z, Xia Y, Zhao Y, Zhang H, et al. Dietary patterns, uric acid levels, and hyperuricemia: a systematic review and meta-analysis. Food Funct. 2023;14(17):7853–68. doi: 10.1039/d3fo02004e [DOI] [PubMed] [Google Scholar]

[pone.0339839.ref042] 42.Choi HK, Curhan G. Soft drinks, fructose consumption, and the risk of gout in men: prospective cohort study. BMJ. 2008;336(7639):309–12. doi: 10.1136/bmj.39449.819271.BE [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0339839.ref043] 43.Vahid F, Hoge A, Hébert JR, Bohn T, ORISCAV working group*. Association of diet quality indices with serum and metabolic biomarkers in participants of the ORISCAV-LUX-2 study. Eur J Nutr. 2023;62(5):2063–85. doi: 10.1007/s00394-023-03095-y [DOI] [PMC free article] [PubMed]

[pone.0339839.ref044] 44.Heindel J, Baid-Agrawal S, Rebholz CM, Nadal J, Schmid M, Schaeffner E, et al. Association Between Dietary Patterns and Kidney Function in Patients With Chronic Kidney Disease: A Cross-Sectional Analysis of the German Chronic Kidney Disease Study. J Ren Nutr. 2020;30(4):296–304. doi: 10.1053/j.jrn.2019.09.008 [DOI] [PMC free article] [PubMed]

[pone.0339839.ref045] 45.Juraschek SP, Gelber AC, Choi HK, Appel LJ, Miller ER 3rd. Effects of the Dietary Approaches to Stop Hypertension (DASH) Diet and Sodium Intake on Serum Uric Acid. Arthritis Rheumatol. 2016;68(12):3002–9. [DOI] [PMC free article] [PubMed]

[pone.0339839.ref046] 46.Angelico F, Baratta F, Coronati M, Ferro D, Del Ben M. Diet and metabolic syndrome: a narrative review. Intern Emerg Med. 2023;18(4):1007–17. doi: 10.1007/s11739-023-03226-7 [DOI] [PubMed] [Google Scholar]

PERMALINK

Uric acid levels mediate the association between four dietary indices and kidney stones in US adults: A cross-sectional study of NHANES 2007–2018

Jinlong Cao

Tianyuan Zhai

Lingyu Guo

Yue Chong

Qi Chen

Qian Wang

Delai Fu

Li Xue

Feng Li

Roles

Abstract

Background

Methods

Results

Conclusion

1. Introduction

2. Methods

2.1 Study population and design

Fig 1. Flowchart of the study.

2.2 Dietary indices

2.3 Definition of kidney stones

2.4 Mediation variables assessment

2.5 Covariate assessment

2.6 Statistical analysis

Table 1. Baseline characteristics of included participants.

3. Results

3.1 Baseline characteristics of the participants

3.2 Association between dietary index and risk of kidney stones

Table 2. Multiple logistic regression analysis between four dietary indices and kidney stones.

3.3 Non-linearity and threshold effect analysis between dietary index and risk of kidney stones

Fig 2. The exposure-response association of the dietary indices with the kidney stone by restricted cubic spline (RCS).

3.4 Association of mixed effects of dietary index with kidney stones evaluated by WQS

Fig 3. Mixed effects and total effects of four dietary indices on kidney stone.

3.5 BKMR model to assess the effect of dietary index on kidney stones

Fig 4. Bivariate exposure–response functions of dietary indices with the kidney stone.

3.6 Intermediation effect analysis

Table 3. The linear regression results of four dietary indices and uric acid.

Fig 5. Uric acid mediates the associations between dietary indices and the risk of kidney stone.

4. Discussion

5. Conclusion

Supporting information

Data Availability

Funding Statement

References

Decision Letter 0

Yogesh Jain

Roles

Author response to Decision Letter 1

Decision Letter 1

Yogesh Jain

Roles

Author response to Decision Letter 2

Decision Letter 2

Yogesh Jain

Roles

Acceptance letter

Yogesh Jain

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

Similar articles

Cited by other articles

Links to NCBI Databases