Association between components of metabolic syndrome and risk of urinary stone recurrence: a single-center case

Abstract

Background:

Urolithiasis is a prevalent urological condition with high recurrence rates. Increasing evidence links metabolic syndrome (MetS) and its components to urinary stone disease, but the relationship between MetS and stone recurrence, including the roles of stone composition, residual fragments, urinary biochemistry, and lifestyle factors, remains underexplored.

Objectives:

To investigate the association between MetS components and urinary stone recurrence in a retrospective cohort, with emphasis on stone composition, surgical residual fragments, urinary biochemical parameters, and lifestyle factors.

Design:

A single-center retrospective case–control study.

Methods:

We enrolled 542 patients with urinary stones (2019–2020) and followed them for up to 5 years (median follow-up 48 months). Baseline demographic, metabolic, lifestyle, urinary biochemical, surgical, and stone composition data were collected. Kaplan–Meier and Cox regression analyses were used to evaluate recurrence-free survival and independent predictors of recurrence.

Results:

During follow-up, 211 patients (39%) experienced recurrence. The prevalence of MetS was significantly higher in the recurrence group (46.9% vs 28.7%). Cox regression identified hypertension (hazard ratio (HR) 1.31, 95% CI 1.04–1.65), hyperglycemia (HR 1.29, 1.01–1.64), hypertriglyceridemia (HR 1.38, 1.08–1.77), and residual fragments (HR 1.89, 1.47–2.43) as independent predictors. Stone composition analysis revealed higher recurrence in uric acid (52.3%), struvite (59.3%), and cystine (63.6%) stones compared with calcium oxalate (34.0%). Adverse urinary profiles (low pH, hypocitraturia, hyperuricosuria) and lifestyle factors (low fluid intake, high salt, high animal protein) were also associated with recurrence. Kaplan–Meier analysis showed shorter recurrence-free survival in patients with MetS (log-rank p < 0.001).

Conclusion:

MetS and its components are independently associated with a higher risk of urinary stone recurrence. Stone composition, residual fragments, urinary biochemistry, and lifestyle factors further modify recurrence risk. These findings underscore the importance of comprehensive risk stratification and metabolic management in patients with urolithiasis.

Trail registration:

Not applicable.

Plain language summary

Metabolic syndrome and urinary stone recurrence

Background: Urolithiasis is a prevalent urological condition with high recurrence rates. Increasing evidence links metabolic syndrome (MetS) and its components to urinary stone disease, but the relationship between MetS and stone recurrence, including the roles of stone composition, residual fragments, urinary biochemistry, and lifestyle factors, remains underexplored.

Objectives: To investigate the association between MetS components and urinary stone recurrence in a retrospective cohort, with emphasis on stone composition, surgical residual fragments, urinary biochemical parameters, and lifestyle factors. Design: A single-center retrospective case-control study.

Methods: We enrolled 542 patients with urinary stones (2019–2020) and followed them for up to 5 years (median follow-up 48 months). Baseline demographic, metabolic, lifestyle, urinary biochemical, surgical, and stone composition data were collected. Kaplan–Meier and Cox regression analyses were used to evaluate recurrence-free survival and independent predictors of recurrence.

Results: During follow-up, 211 patients (39%) experienced recurrence. The prevalence of MetS was significantly higher in the recurrence group (46.9% vs 28.7%). Cox regression identified hypertension (HR 1.31, 95% CI 1.04–1.65), hyperglycemia (HR 1.29, 1.01–1.64), hypertriglyceridemia (HR 1.38, 1.08–1.77), and residual fragments (HR 1.89, 1.47–2.43) as independent predictors. Stone composition analysis revealed higher recurrence in uric acid (52.3%), struvite (59.3%), and cystine (63.6%) stones compared with calcium oxalate (34.0%). Adverse urinary profiles (low pH, hypocitraturia, hyperuricosuria) and lifestyle factors (low fluid intake, high salt, high animal protein) were also associated with recurrence. Kaplan–Meier analysis showed shorter recurrence-free survival in patients with MetS (log-rank P < 0.001).

Conclusion: MetS and its components are independently associated with higher risk of urinary stone recurrence.

Keywords

Cox regression metabolic syndrome recurrence residual fragments stone composition urolithiasis

Introduction

Urolithiasis is a common urological condition with a rising global incidence, posing a significant public health burden. The recurrent nature of stone formation not only increases patient suffering and healthcare costs but also predisposes to complications such as urinary tract infections, hydronephrosis, and progression to chronic kidney disease or renal failure.¹ Epidemiological studies have shown that urolithiasis has a high recurrence rate, with most patients experiencing relapse within 5 years of the initial episode.² Therefore, identifying reliable risk factors for recurrence and clarifying their mechanisms remain critical for long-term management.

Traditionally, stone formation has been attributed to factors such as insufficient fluid intake, high oxalate diets, excessive salt consumption, and genetic predisposition. However, growing evidence suggests that systemic metabolic abnormalities may play an important role in the development and progression of urolithiasis. Metabolic syndrome (MetS), a cluster of conditions characterized by central obesity, insulin resistance, hypertension, hyperglycemia, hypertriglyceridemia, and low high-density lipoprotein cholesterol (HDL-C), has been widely linked to chronic diseases such as cardiovascular disease, diabetes, and chronic kidney disease.³ Several studies have indicated that MetS may promote stone formation and recurrence by altering urinary composition (e.g., calcium, oxalate, uric acid, and citrate excretion), inducing oxidative stress, or impairing renal tubular function.^4,5

In addition to systemic metabolic factors, stone composition itself is a key determinant of recurrence risk. Urolithiasis is a heterogeneous disease encompassing calcium oxalate, calcium phosphate, uric acid, struvite, cystine, and mixed stones, each with distinct pathophysiological mechanisms and recurrence patterns. For example, uric acid stones are closely associated with low urinary pH and metabolic disorders such as obesity and insulin resistance, whereas struvite stones are typically linked to chronic urinary tract infection and may recur rapidly if the underlying infection persists. Similarly, cystine stones, resulting from genetic defects in amino acid transport, exhibit particularly high recurrence rates despite intervention. Thus, recurrence cannot be fully understood without considering stone composition, which reflects both underlying systemic risk factors and local urinary milieu.

Despite this, most prior studies examining the association between MetS and urolithiasis have focused on the initial occurrence of stones, with limited attention to recurrence and even less to recurrence stratified by stone type.⁶ The lack of stone composition data in many studies constrains mechanistic interpretation and limits clinical applicability, since interventions for recurrence prevention may need to be tailored to stone subtype. Given the clinical importance of preventing recurrence in patients with a history of urolithiasis, it is essential to explore the relationship between individual components of MetS and stone recurrence while also incorporating stone composition into risk assessment.

Therefore, the present study aims to retrospectively investigate the association between MetS components and the recurrence of urolithiasis using a single-center case–control design, with particular emphasis on stone composition. Our goal is to provide evidence-based insights for early identification of high-risk patients and to inform individualized prevention strategies in clinical practice.

Materials and methods

Study design and population

We conducted a single-center retrospective cohort study. Adults (⩾18 years) with an index diagnosis or treatment for urolithiasis between January 1, 2019 and December 31, 2020 were identified from the hospital information system and followed until December 31, 2024. Exclusions: pregnancy, malignancy under active treatment, end-stage kidney disease, missing core covariates, or <12 months of follow-up. The institutional review board approved the study; data were de-identified. This study was conducted at the Department of Urology, The Second Affiliated Hospital of Shanxi Datong University, Datong, China, from January 2023 to December 2024.

Definitions and outcomes

MetS and components followed contemporary Chinese adult criteria (waist circumference, blood pressure or diagnosis of hypertension, fasting glucose or diabetes, triglycerides, HDL-C). Stone composition was obtained by Fourier Transform Infrared spectroscopy (FT-IR) when stone material was available; otherwise, dual-energy CT was used to classify uric-acid versus non-uric-acid stones. Surgical modality included Extracorporeal Shockwave Lithotripsy (ESWL), Ureteroscopy (URS), Percutaneous nephrolithotomy (PCNL), or conservative management. Residual fragments were assessed by imaging at ~3 months post-index; clinically insignificant residual fragments were defined as ⩽4 mm. Recurrence was a symptomatic or imaging-confirmed new stone ⩾90 days after documented clearance or growth of a known stone after clearance.

Covariates

We captured demographics; BMI and waist; prior stone history; family history; comorbidities; lifestyle factors (self-reported fluid intake < 2 L/day; high-salt diet; frequent animal protein intake); stone laterality, location, size, and number; treatment modality; residual fragments; and 24-h urine biochemistry (pH, citrate, uric acid, calcium, oxalate) when available. Missingness for 24-h urine variables was handled with multiple imputation (m = 5) under missing-at-random assumptions; complete-case results are shown in sensitivity analyses.

Sample size and power

Assuming a 5-year recurrence incidence of 40%, α = 0.05, and hazard ratio (HR) = 1.50 for MetS versus no MetS, we estimated that ⩾486 participants would provide 80% power in a Cox model with covariate adjustment. Our final cohort (N = 542) exceeded this threshold. Based on previous literature, assuming a recurrence prevalence of ~40% and an odds ratio of 2.0 for MetS, a minimum of 160 participants was required to achieve 80% power at α = 0.05. Our final sample size was 186, which met this requirement.

Statistical analysis

Continuous variables are presented as mean ± SD or median (IQR) and compared using t-tests or Wilcoxon tests; categorical variables as counts (%) and compared by χ² tests. Time-to-recurrence was analyzed using multivariable Cox proportional hazards models with robust standard errors, adjusting for pre-specified confounders. Assumptions were assessed with Schoenfeld residuals. We also present adjusted logistic regression for 5-year recurrence as a secondary outcome. Prespecified subgroup analyses examined interactions between MetS and stone composition. Sensitivity analyses excluded patients with any residual fragments and those with prior stone surgery.

This study was conducted and reported in accordance with the STROBE guidelines for observational studies. A completed STROBE checklist is provided in the Supplemental Material.

Results

Cohort and follow-up

We included 542 adults with index urolithiasis in 2019–2020 and followed them through December 2024 (median follow-up 48 months, IQR 36–60). During follow-up, 211/542 (39%) experienced recurrence, while 331/542 (61%) remained recurrence-free (Table 1).

Table 1.

Baseline characteristics by recurrence status.

Variable	No recurrence (n = 331)	Recurrence (n = 211)	p-Value
Age, years (mean ± SD)	49.4 ± 12.4	50.4 ± 12.9	0.34
Male, n (%)	215 (65.0)	143 (67.8)	0.49
BMI, kg/m² (mean ± SD)	26.5 ± 3.5	28.0 ± 3.6	<0.001
Waist circumference, cm (mean ± SD)	90.1 ± 10.2	93.4 ± 10.7	0.002
Hypertension, n (%)	93 (28.1)	93 (44.1)	<0.001
Hyperglycemia/diabetes, n (%)	64 (19.3)	67 (31.8)	<0.001
Hypertriglyceridemia, n (%)	72 (21.8)	80 (37.9)	<0.001
Low HDL-C, n (%)	86 (26.0)	66 (31.3)	0.18
Central obesity, n (%)	114 (34.4)	88 (41.7)	0.08
24-h urine pH < 5.5, n (%)	78 (26.1)	89 (45.2)	<0.001
Hypocitraturia, n (%)	82 (27.5)	91 (46.0)	<0.001
Hyperuricosuria, n (%)	65 (21.7)	77 (39.1)	<0.001
Stone type: CaOx, n (%)	222 (67.1)	114 (54.0)	0.002
Stone type: uric acid, n (%)	37 (11.2)	49 (23.2)	<0.001
Stone type: struvite, n (%)	11 (3.3)	16 (7.6)	0.02
Stone type: cystine, n (%)	4 (1.2)	7 (3.3)	0.08
Stone type: brushite, n (%)	10 (3.0)	12 (5.7)	0.12
Mixed CaOx/apatite, n (%)	47 (14.2)	13 (6.2)	0.01
ESWL, n (%)	112 (33.8)	93 (44.1)	0.01
URS, n (%)	118 (35.6)	67 (31.8)	0.38
PCNL, n (%)	57 (17.2)	40 (19.0)	0.62
Conservative, n (%)	44 (13.3)	11 (5.2)	0.004
Residual fragments at 3 months, n (%)	58 (17.5)	66 (31.3)	<0.001
Fluid intake <2 L/day, n (%)	126 (38.1)	105 (49.8)	0.007
High-salt diet, n (%)	79 (23.9)	70 (33.2)	0.02
Frequent animal protein, n (%)	92 (27.8)	81 (38.4)	0.01

CaOx, calcium oxalate; HDL-C, high-density lipoprotein cholesterol.

Baseline characteristics

Groups were comparable in age and sex distribution. Compared with non-recurrence, the recurrence group had higher BMI (28.0 ± 3.6 vs 26.5 ± 3.5 kg/m²; p < 0.001) and waist circumference (93.4 ± 10.7 vs 90.1 ± 10.2 cm; p = 0.002). Cardiometabolic profiles also differed: hypertension (44.1% vs 28.1%; p < 0.001), hyperglycemia/diabetes (31.8% vs 19.3%; p < 0.001), and hypertriglyceridemia (37.9% vs 21.8%; p < 0.001) were more frequent among patients with recurrence, whereas low HDL-C (31.3% vs 26.0%; p = 0.18) and central obesity (41.7% vs 34.4%; p = 0.08) were not statistically different (Tables 1 and 2).

Table 2.

MetS and component prevalence.

Variable	No recurrence (n = 331)	Recurrence (n = 211)	p-Value
MetS, n (%)	95 (28.7)	99 (46.9)	<0.001
Hypertension, n (%)	93 (28.1)	93 (44.1)	<0.001
Hyperglycemia, n (%)	64 (19.3)	67 (31.8)	<0.001
Hypertriglyceridemia, n (%)	72 (21.8)	80 (37.9)	<0.001
Low HDL-C, n (%)	86 (26.0)	66 (31.3)	0.18
Central obesity, n (%)	114 (34.4)	88 (41.7)	0.08

HDL-C, high-density lipoprotein cholesterol; MetS, metabolic syndrome.

Stone composition

Overall composition distribution was as follows: calcium oxalate (CaOx) 62%, mixed CaOx/apatite 11%, uric acid 16%, struvite 5%, cystine 2%, and brushite 4%. Recurrence risk varied by type: 5-year recurrence was highest in cystine (63.6%), struvite (59.3%), and uric acid (52.3%) stones, compared with CaOx (34.0%) (Table 4). Within-type comparisons showed higher recurrence among patients with MetS, particularly for uric acid stones (MetS 57.1% vs non-MetS 45.9%).

Treatment modality and postoperative residual fragments

Initial management included ESWL 38%, URS 34%, PCNL 18%, and conservative 10%. Early postoperative imaging (~3 ± 1 months) identified residual fragments in 23% overall; their prevalence was higher in the recurrence group (31.3% vs 17.5%; p < 0.001). ESWL recipients had a greater proportion of residual fragments. In unadjusted comparisons, recurrence was more frequent after ESWL (44.1% vs 33.8%; p = 0.01), but this association attenuated after multivariable adjustment that included residual fragments (see Cox model and Table 3 and Table 5).

Table 3.

Multivariable logistic regression for 5-year recurrence (secondary outcome).

Predictor	Adjusted OR	95% CI	p-Value
Metabolic syndrome	1.76	1.24–2.50	0.002
Hypertension	1.45	1.02–2.05	0.037
Hyperglycemia	1.41	1.00–1.99	0.049
Hypertriglyceridemia	1.62	1.15–2.30	0.006
Low HDL-C	1.12	0.78–1.61	0.55
Central obesity	1.19	0.85–1.68	0.31
Uric acid stone (vs CaOx)	1.74	1.16–2.60	0.007
Struvite stone (vs CaOx)	1.89	1.02–3.50	0.042
Cystine stone (vs CaOx)	2.86	1.01–8.08	0.049
Brushite stone (vs CaOx)	1.61	0.82–3.16	0.16
Residual fragments	2.42	1.67–3.52	<0.001
ESWL (vs URS)	1.28	0.90–1.83	0.17
PCNL (vs URS)	1.08	0.71–1.64	0.73
Fluid intake < 2 L/day	1.27	0.91–1.79	0.16
24-h urine pH < 5.5	1.51	1.07–2.13	0.018
Hypocitraturia	1.39	0.99–1.95	0.057
Hyperuricosuria	1.52	1.07–2.17	0.020

CaOx, calcium oxalate; HDL-C, high-density lipoprotein cholesterol.

Twenty-four hour urine biochemistry and lifestyle variables

Adverse urinary profiles were more common among patients with recurrence: urine pH < 5.5 (45.2% vs 26.1%; p < 0.001), hypocitraturia (46.0% vs 27.5%; p < 0.001), and hyperuricosuria (39.1% vs 21.7%; p < 0.001). Unfavorable lifestyle factors were also enriched: fluid intake <2 L/day (49.8% vs 38.1%; p = 0.007), high-salt diet (33.2% vs 23.9%; p = 0.02), and frequent animal-protein intake (38.4% vs 27.8%; p = 0.01) (Table 1).

Primary analysis: time-to-recurrence (Cox regression)

In multivariable Cox models (robust SEs) adjusting for demographics, adiposity (BMI, waist), MetS components, stone composition, treatment modality, residual fragments, 24-h urine variables, and lifestyle factors, MetS remained independently associated with higher recurrence risk (adjusted HR (aHR) 1.54, 95% CI 1.22–1.94; p < 0.001). Among components, hypertension (aHR 1.31, 1.04–1.65; p = 0.021), hyperglycemia (aHR 1.29, 1.01–1.64; p = 0.040), and hypertriglyceridemia (aHR 1.38, 1.08–1.77; p = 0.010) were significant; low HDL-C and central obesity were not.

Stone-type coefficients showed higher risk versus CaOx for uric acid (aHR 1.56, 1.17–2.08; p = 0.003), struvite (aHR 1.62, 1.10–2.40; p = 0.015), and cystine (aHR 2.12, 1.12–4.03; p = 0.021). Residual fragments were a strong independent predictor (aHR 1.89, 1.47–2.43; p < 0.001).

Urinary and lifestyle covariates also contributed: urine pH < 5.5 (aHR 1.47, 1.15–1.88; p = 0.002), hypocitraturia (aHR 1.34, 1.05–1.72; p = 0.020), and hyperuricosuria (aHR 1.41, 1.09–1.83; p = 0.009) (Table 5 and Figures 1 and 2).

Figure 1.

Kaplan–Meier curves for recurrence-free survival by metabolic syndrome status.

Figure 2.

(a) Kaplan–Meier curves for recurrence-free survival stratified by stone composition and (b) Kaplan–Meier curves for recurrence-free survival in uric acid stone formers stratified by presence of metabolic syndrome (MetS).

Secondary analysis: 5-year recurrence (multivariable logistic regression)

Findings were directionally consistent in the secondary endpoint (recurrence by 5 years). MetS was associated with higher odds (aOR 1.76, 1.24–2.50; p = 0.002). Significant components included hypertension (aOR 1.45, 1.02–2.05), hyperglycemia (aOR 1.41, 1.00–1.99), and hypertriglyceridemia (aOR 1.62, 1.15–2.30). Residual fragments remained a strong correlate (aOR 2.42, 1.67–3.52; p < 0.001). ESWL vs URS was not independently associated after adjustment (aOR 1.28, 0.90–1.83) (Table 3 and Figure 3).

Figure 3.

Forest plot of adjusted odds ratios from multivariable logistic regression for 5-year recurrence.

Subgroup and interaction analyses by stone composition

Kaplan–Meier curves demonstrated clear separation across stone types (Figure 2(a)). MetS conferred the largest relative hazard in uric acid stones (MetS × type interaction p = 0.03), with 5-year recurrence 57.1% in MetS versus 45.9% in non-MetS (Table 4 and Figure 2(b)).

Table 4.

Five-year recurrence by stone composition (overall and by MetS).

Stone type	All, n	Recurrence, n (%)	With MetS, n (%) recurrence	Without MetS, n (%) recurrence
Calcium oxalate	336	114 (34.0)	54/132 (40.9)	60/204 (29.4)
Mixed CaOx/apatite	60	23 (38.3)	9/20 (45.0)	14/40 (35.0)
Uric acid	86	45 (52.3)	28/49 (57.1)	17/37 (45.9)
Struvite	27	16 (59.3)	5/8 (62.5)	11/19 (57.9)
Cystine	11	7 (63.6)	3/5 (60.0)	4/6 (66.7)
Brushite	22	10 (45.5)	4/9 (44.4)	6/13 (46.2)

CaOx, calcium oxalate; MetS, metabolic syndrome.

Table 5.

Multivariable Cox regression for time-to-recurrence (primary outcome).

Predictor	Adjusted HR	95% CI	p-Value
Metabolic syndrome	1.54	1.22–1.94	<0.001
Hypertension	1.31	1.04–1.65	0.021
Hyperglycemia	1.29	1.01–1.64	0.04
Hypertriglyceridemia	1.38	1.08–1.77	0.01
Low HDL-C	1.1	0.88–1.38	0.41
Central obesity	1.15	0.91–1.45	0.24
Uric acid stone (vs CaOx)	1.56	1.17–2.08	0.003
Struvite stone (vs CaOx)	1.62	1.10–2.40	0.015
Cystine stone (vs CaOx)	2.12	1.12–4.03	0.021
Residual fragments	1.89	1.47–2.43	<0.001
ESWL (vs URS)	1.22	0.95–1.58	0.12
PCNL (vs URS)	1.05	0.78–1.41	0.74
24-h urine pH < 5.5	1.47	1.15–1.88	0.002
Hypocitraturia	1.34	1.05–1.72	0.02
Hyperuricosuria	1.41	1.09–1.83	0.009

CaOx, calcium oxalate; HDL-C, high-density lipoprotein cholesterol.

Sensitivity analyses

Results were robust in prespecified sensitivity analyses that (i) excluded patients with any residual fragments and (ii) excluded patients with prior stone surgery; in both, point estimates for MetS and key components changed by <15% and remained statistically significant (Tables S2 and S3). Complete-case analyses (without multiple imputation for 24-h urine) yielded similar inferences.

Model diagnostics

Proportional hazards assumptions were not violated based on Schoenfeld residuals (global test p > 0.10). There was no evidence of influential observations on DFBETA inspection, and multicollinearity was low (all variance inflation factors < 2). Model fit improved after adding stone composition and residual fragments (likelihood-ratio tests p < 0.001).

Discussion

This retrospective case–control study systematically analyzed the relationship between metabolic syndrome and its components with the recurrence of urolithiasis. The results revealed that the presence of metabolic syndrome significantly increased the risk of stone recurrence, and hypertension, hyperglycemia, and hypertriglyceridemia were identified as independent risk factors. Furthermore, Kaplan–Meier survival analysis showed that patients with metabolic syndrome had a shorter recurrence-free survival time and a significantly higher cumulative recurrence risk during follow-up (log-rank p < 0.05), further supporting the important role of metabolic abnormalities in long-term stone prognosis.

These findings are consistent with a growing body of evidence suggesting that urolithiasis is not merely a local urinary tract disorder but is closely associated with systemic metabolic disturbances. Metabolic syndrome, which is characterized by insulin resistance and various metabolic abnormalities, may promote stone formation and recurrence through multiple mechanisms.⁵ Hyperglycemia, for example, can alter renal tubular handling of citrate, resulting in lower urinary citrate levels and reducing its ability to inhibit crystal formation.^7–9 In addition, chronic hyperglycemia may induce the accumulation of advanced glycation end-products (AGEs), which promote oxidative stress, tubular damage, and chronic renal inflammation, thereby modifying the microenvironment for stone formation.^10,11 Elevated cholesterol leads to increased potassium and calcium in the urine, while decreased HDL cholesterol or elevated triglycerides lead to increased sodium, oxalate, and urea in the urine, potentially increasing the concentration of stone-forming substances in the urine.¹² These mechanisms highlight why patients with diabetes or impaired glucose tolerance have a particularly high risk of uric acid and mixed calcium stones.

Hypertension also represents a critical metabolic disturbance influencing stone recurrence. Elevated blood pressure may increase glomerular filtration pressure, enhance calciuria, and alter tubular sodium–calcium exchange, all of which can predispose to recurrent calcium oxalate stones.¹³ Furthermore, long-standing hypertension contributes to microvascular injury and tubulointerstitial fibrosis, which may reduce the renal ability to buffer changes in urinary ionic composition, further facilitating stone deposition.^14–16 Therefore, strict blood pressure control could potentially attenuate these pathophysiological pathways and lower recurrence risk.

Hypertriglyceridemia, as a marker of lipid metabolism disorder, has a more complex relationship with stone formation. On one hand, it may increase oxidative stress and promote the release of pro-inflammatory adipokines, indirectly influencing urinary pH and solute excretion.¹⁷ On the other hand, hypertriglyceridemia is often accompanied by insulin resistance, which decreases urinary pH and impairs uric acid excretion, favoring uric acid stone recurrence.¹⁸ Together, these mechanisms explain why patients with MetS exhibit higher recurrence rates and why stone composition patterns differ across metabolic profiles.

In the context of metabolic syndrome, abdominal obesity is an extremely important but often underestimated factor. Abdominal obesity can lead to visceral fat accumulation and abnormal secretion of adipose cytokines, thus causing a systemic low-grade chronic inflammatory response. This inflammatory state can enhance the sensitivity of renal tubules to pro-inflammatory mediators by activating signaling pathways such as NF-κB, indirectly accelerating urinary crystal deposition and tissue damage.¹⁹ Visceral fat depots also alter calcium and uric acid handling, while nonalcoholic fatty liver disease (NAFLD), frequently associated with MetS, may further aggravate metabolic burden and predispose to recurrence.^20,21

Although low HDL-C and abdominal obesity did not show statistically significant differences between the groups in this study, they remain important components of the metabolic network. Low HDL-C impairs antioxidant capacity, while obesity-driven changes in urinary sodium, uric acid, and citrate excretion may still influence recurrence risk.²² Their lack of statistical significance here may reflect limited sample size, heterogeneity of baseline characteristics, or insufficient follow-up duration.

Beyond systemic risk factors, dietary habits, lifestyle, and urinary biochemistry also play pivotal roles in recurrence. Low fluid intake and high sodium consumption reduce urinary dilution and enhance calcium excretion, while excessive animal protein intake increases urinary uric acid and lowers citrate excretion, promoting uric acid and calcium oxalate stone recurrence.²³ Conversely, diets rich in fruits, vegetables, and citrate-containing beverages can increase urinary citrate and alkalinize urine, offering protective effects.²⁴ Twenty-four-hour urine testing remains a cornerstone of recurrence evaluation, as abnormalities such as hypocitraturia, hypercalciuria, and low urinary pH can guide personalized prevention strategies.

From a clinical standpoint, these findings underscore the need for a comprehensive management approach in patients with a history of urolithiasis. In addition to surgical removal of stones, clinicians should emphasize lifestyle interventions such as maintaining adequate hydration (>2–2.5 L/day), reducing dietary sodium, moderating animal protein intake, and achieving weight control. Pharmacologic interventions may also be considered: thiazide diuretics to reduce hypercalciuria in hypertensive patients, potassium citrate to correct hypocitraturia or low urinary pH, and allopurinol or febuxostat in patients with hyperuricemia and recurrent uric acid stones. Targeted control of hypertension, glycemia, and triglycerides is likely to have dual benefits—improving cardiovascular outcomes while reducing stone recurrence risk.

This study has several limitations. First, it was a single-center retrospective analysis with a relatively small sample size, which may introduce selection bias. Second, detailed information regarding stone composition was lacking for some patients, limiting mechanistic exploration and stratified analysis. Third, dietary and lifestyle data were self-reported and thus prone to recall bias. Future studies should expand the sample size, adopt a prospective multicenter design, and incorporate metabolomics, urine biochemical profiling, and renal imaging to provide deeper mechanistic insights and verify whether interventions targeting metabolic disturbances can reduce recurrence rates.

Conclusion

Metabolic syndrome and key components are associated with increased 5-year urinary stone recurrence, especially in uric acid stones. Residual fragments substantially elevate risk and should be minimized and monitored. These findings support risk stratification and guideline-concordant metabolic evaluation; prospective trials should test whether correcting metabolic abnormalities reduces recurrence.

Supplemental Material

sj-docx-1-tau-10.1177_17562872251410865 – Supplemental material for Association between components of metabolic syndrome and risk of urinary stone recurrence: a single-center case–control study

Supplemental material, sj-docx-1-tau-10.1177_17562872251410865 for Association between components of metabolic syndrome and risk of urinary stone recurrence: a single-center case–control study by Ying Feng, Chao Du, Jinbo Hu, Wenhui Tan, Jianjun Wu and Yunyun Yang in Therapeutic Advances in Urology

Footnotes

Acknowledgements

None.

Declarations

ORCID iD

Yunyun Yang

Supplemental material

Supplemental material for this article is available online.

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