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Non-linear association between visceral adipose tissue area and serum uric acid concentration in US adults: findings from NHANES 2011–2018

BMC Public Health volume 25, Article number: 1405 (2025) Cite this article

Abstract

Background

Research on the relationship between visceral adipose tissue (VAT) and serum uric acid (SUA) in the general population remains limited. This study aims to comprehensively examine the association between VAT area and SUA concentrations in a representative sample of U.S. adults.

Methods

Data were drawn from the National Health and Nutrition Examination Survey (NHANES) spanning 2011 to 2018. A total of 10,514 participants aged 18 to 59 years were included in the analysis. VAT area was measured using dual-energy X-ray absorptiometry (DXA) scans, and SUA levels were collected at mobile examination centers. Multivariable linear regression models were employed to assess the association between VAT and SUA. Restricted cubic splines (RCS) were used to detect potential non-linear relationships. Subgroup analyses were conducted based on age, sex, drinking status, and renal function to test the robustness of the findings.

Results

The median VAT area and SUA concentration were 91.24 cm² and 5.2 mg/dL, respectively. In the unadjusted model, each standard deviation (SD) increase in VAT was positively associated with SUA (β = 0.43; 95% CI: 0.39–0.47). After adjusting for covariates, this positive association remained consistent across all models. RCS analysis revealed a non-linear relationship (P for non-linearity < 0.001), with a stronger association observed when VAT was below 3.3 SDs. Significant interactions were identified in age and sex subgroups (P for interaction < 0.05).

Conclusion

This study demonstrates a positive, non-linear association between VAT area and SUA concentrations in young and middle-aged U.S. adults. The observed threshold effect provides valuable insight for clinicians in stratifying risks for hyperuricemia and related comorbidities, particularly among individuals with elevated VAT levels.

Peer Review reports

Introduction

Obesity is a growing public health concern worldwide, with prevalence rates steadily increasing over the past decades. According to a previous meta-analysis, obesity rates have increased nearly 4.5 times since 1990, affecting over 870 million adults globally in 2022 [1]. One of the key components of obesity is the accumulation of visceral adipose tissue (VAT), a type of fat that is stored deep in the abdominal cavity surrounding vital organs [2]. Excessive VAT is associated with a wide range of metabolic disorders, including insulin resistance [3], type 2 diabetes [4], hypertension [5], cardiovascular diseases [6], and cancers [7]. The harmful effects of visceral fat are primarily attributed to its role in promoting systemic inflammation and abnormal lipid metabolism, making it a critical target for obesity-related disease prevention and management [8].

Serum uric acid (SUA) is a byproduct of purine metabolism and is commonly used as a biomarker for assessing metabolic health [9, 10]. Elevated levels of SUA, a condition known as hyperuricemia, are associated with an increased risk of developing gout [11], kidney failure [12], hypertension [13], and metabolic syndrome [14]. Additionally, high SUA levels have been suggested to promote oxidative stress and endothelial dysfunction, further contributing to the development of atherosclerosis and other cardiovascular complications [15].

Recent studies have explored the relationship between VAT and SUA, as both are closely tied to metabolic dysfunction. However, some of these studies merely conducted intergroup comparisons and calculated Pearson correlation coefficients without implementing comprehensive modeling approaches to thoroughly examine the association between VAT and SUA [16, 17]. Furthermore, most research has focused on specific demographic groups or used small sample sizes, limiting the generalizability of the results [18, 19]. Therefore, a more comprehensive understanding of the interaction between VAT and SUA is necessary, particularly in diverse populations.

This study aims to address these gaps by examining the association between VAT and SUA using data from the National Health and Nutrition Examination Survey (NHANES). We hypothesize that increased visceral fat is significantly associated with elevated SUA levels and that this relationship may vary according to demographic and metabolic factors. By utilizing a large, nationally representative dataset, we aim to provide a more robust analysis of this association and contribute to the understanding of the metabolic implications of VAT accumulation and SUA concentrations.

Methods and materials

Study population

In this study, 23,825 participants aged 18 and older from the NHANES 2011–2018 dataset were initially considered. Participants missing data on VAT or SUA were excluded, followed by those lacking information on education, poverty-income ratio (PIR), smoking status, drinking behavior, or body mass index (BMI). Ultimately, 10,514 participants were included in the final analysis (see Fig. 1). The National Center for Health Statistics (NCHS) implemented rigorous measures to ensure participant privacy and confidentiality. The NHANES study was approved by the NCHS Ethics Review Board under Protocol #2011-17 and Protocol #2018-01 [20].

Fig. 1
figure 1

Flowchart detailing the inclusion of participants from the NHANES data collected between 2011 and 2018. Abbreviation: BMI, body mass index; NHANES, National Health and Nutrition Examination Survey; SUA, serum uric acid; VAT, visceral adipose tissue

Full size image

Measurement of VAT area

Between 2011 and 2018, whole-body dual-energy X-ray absorptiometry (DXA) scans were conducted at the NHANES Mobile Examination Center (MEC). VAT was assessed using the Hologic APEX software [21], which analyzed the fat area within the abdominal cavity. Specifically, VAT measurements were taken around the intervertebral space between the L4 and L5 vertebrae. Rigorous quality control protocols were followed throughout the data collection and analysis process to ensure accuracy and consistency [22].

Measurement of SUA

SUA concentration testing was carried out in MECs located across various regions in the United States. SUA levels were determined using the enzymatic uricase method, a standard approach for measuring uric acid concentration. In this method, uricase oxidizes uric acid to produce allantoin and hydrogen peroxide, and the resulting hydrogen peroxide is measured to quantify SUA levels [23, 24]. Analyses were conducted in certified laboratories that adhered to strict quality control standards. SUA concentrations in this study were reported in mg/dl.

Covariates

In this study, several covariates were selected for analysis due to their potential associations with SUA levels. This included age (in years), sex (male or female, based on participant self-reporting), and ethnicity (categorized as Non-Hispanic White, Non-Hispanic Black, Mexican American, Other Hispanic, and Other Races, which includes individuals of mixed race). Education level was classified into three groups: less than high school, high school graduate, and college graduate or higher. The PIR was grouped as ≤ 1.3 (indicating poverty), 1.3–3.5, and > 3.5. Smoking status was defined as never smokers, former smokers (those who have smoked at least 100 cigarettes in their lifetime but do not currently smoke), and current smokers. Alcohol consumption categories defined drinkers as males consuming ≥ 2 drinks per day or females consuming ≥ 1 drink per day [25]. Physical activity was categorized based on participation in recreational activities. BMI was calculated in kg/m², which is derived from weight in kilograms divided by height in meters squared. Additionally, the estimated glomerular filtration rate (eGFR) was assessed using the 2009 CKD-EPI (Chronic Kidney Disease Epidemiology Collaboration) equation [26].

Statistical analysis

Data analysis was conducted between September and October 2024, using sampling weights provided by NHANES. Continuous variables are reported as means with standard errors (SE), while categorical variables are presented as proportions with weighted percentages of the total sample. To analyze participant characteristics across VAT area tertiles, one-way ANOVA was applied for continuous variables, and chi-square tests were used for categorical variables.

The association between VAT area and SUA was assessed using linear regression models, providing regression coefficients (β) with 95% confidence intervals (CI). Three models were estimated: Model 1 adjusted for age, sex, and ethnicity; Model 2 additionally adjusted for education level, PIR, smoking status, alcohol consumption, and physical activity; and Model 3 included further adjustments for BMI and eGFR. Confounding variables were selected based on previous research and clinical expertise [27, 28]. Trend analyses were performed using multivariable regression, treating the median values of VAT tertiles as continuous variables.

For subgroup analyses, stratified linear regression models were conducted by age (< 40 vs. ≥40 years), sex, alcohol consumption, and eGFR (< 60 vs. ≥60 mL/min/1.73 m²). Interaction terms were tested using likelihood ratio tests to explore potential effect modification across subgroups.

To assess the dose-response relationship, restricted cubic splines (RCS) with knots at the 5th, 50th, and 95th percentiles of the VAT distribution were applied in both the unadjusted and fully adjusted (Model 3) linear regression models. Additionally, two-piecewise linear regression was used to identify potential inflection points.

No imputation was applied to the dataset. All analyses were performed using R version 4.3.2 (http://www.R-project.org, The R Foundation) in combination with Free Statistics software version 1.9.2. Statistical significance was defined as a two-sided p-value < 0.05.

Results

Distribution of weighted characteristics for NHANES participants (2011–2018) based on tertiles of VAT area

In this study, the mean participant age was 38.26 years, with median VAT and SUA values of 91.24 cm² and 5.2 mg/dL, respectively. Participants in the highest VAT tertile were typically older, had a higher obesity prevalence, and were more likely to be male and non-Hispanic White. As VAT levels increased, the proportion of participants with higher education, current smoking status, alcohol use, physical activity, and eGFR levels declined. No significant differences in PIR were observed across VAT tertiles. These findings are detailed in Table 1.

Table 1 Distribution of weighted characteristics for NHANES participants (2011–2018) based on tertiles of VAT area
Full size table

Association between VAT area and SUA concentration among adults in NHANES 2011–2018

In the univariable analysis, each standard deviation (SD) increase in VAT was associated with higher SUA levels (β: 0.43, 95% CI: 0.39–0.47). Compared to the first VAT tertile, participants in the second and third tertiles exhibited higher SUA levels, with β (95% CI) values of 0.56 (0.49–0.64) and 1.05 (0.96–1.13), respectively. Detailed results on the univariable associations are presented in Supplementary Table 1.

In the multivariable analysis, the association between VAT and SUA remained significant. For every SD increase in VAT, the β (95% CI) was 0.45 (0.42–0.49) in Model 1, 0.46 (0.42–0.50) in Model 2, and 0.25 (0.20–0.30) in Model 3. Compared to the lowest VAT tertile, the second and third tertiles were associated with higher SUA concentrations. In Model 1, the β (95% CI) values were 0.57 (0.51–0.62) and 1.10 (1.03–1.17); in Model 2, they were 0.57 (0.51–0.63) and 1.12 (1.05–1.19); and in Model 3, the values were 0.30 (0.23–0.37) and 0.61 (0.50–0.71). The corresponding results are summarized in Table 2.

Table 2 Multivariable linear regression analysis of the association between VAT area and serum UA among adults in NHANES 2011–2018
Full size table

Subgroup analysis of the association between VAT and SUA in adults in NHANES 2011–2018

As shown in Fig. 2, the positive association between VAT (per SD) and SUA was consistent across all subgroups. This association was notably stronger in participants under 40 years of age (P for interaction < 0.001) and in females (P for interaction = 0.001).

Fig. 2
figure 2

Analysis of subgroups regarding the association between VAT area and SUA concentration in adults based on NHANES data from 2011 to 2018. Each model in the subgroups was adjusted for age, sex, ethnicity, education, poverty-income ratio, smoking, drinking, physical activity, BMI, and eGFR, excluding the stratified variable itself. Abbreviations: BMI, body mass index; CI, confidence interval; eGFR, estimated glomerular filtration rate; NHANES, National Health and Nutrition Examination Survey; SUA, serum uric acid; VAT, visceral adipose tissue

Full size image

Non-linear association between VAT area and SUA concentration among adults in NHANES 2011–2018

The RCS analysis revealed a non-linear relationship between VAT (SD) and SUA (P for non-linearity < 0.001). When VAT was below 3.3 SDs, the positive association between VAT and SUA was significant, with β (95% CI) values of 0.56 (0.52–0.60) in the unadjusted model and 0.34 (0.28–0.39) in the adjusted model. However, when VAT exceeded 3.3 SDs, the association lost statistical significance. These results are presented in Fig. 3; Table 3.

Fig. 3
figure 3

Restricted Cubic Spline Analysis Demonstrates a Nonlinear Positive Association of VAT Area with SUA Concentration in Adults from NHANES 2011–2018. A restricted cubic spline with three knots at the 5th, 50th, and 95th percentiles of the VAT (SD) distribution. The predicted β values for SUA concentration, along with their 95% CIs, are shown by the solid blue line and the shaded regions. The model was adjusted for age, sex, ethnicity, education, poverty-income ratio, smoking, drinking, physical activity, BMI, and eGFR. Abbreviations: BMI, body mass index; CI, confidence interval; eGFR, estimated glomerular filtration rate; NHANES, National Health and Nutrition Examination Survey; SD, standard deviation; SUA, serum uric acid; VAT, visceral adipose tissue

Full size image
Table 3 Examination of the association between VAT and serum UA in NHANES adults (2011–2018) using two-piecewise regression approaches
Full size table

Discussion

In this study, we identified a positive association between VAT area and SUA concentrations among young and middle-aged adults in the United States. This association was notably stronger when the VAT area was below 3.3 SDs, approximately 189 cm². Subgroup analysis further indicated that the positive association was more pronounced in females and participants under 40 years of age.

Our findings align with previous studies that have reported a positive association between VAT area and SUA levels. For instance, a study involving 867 patients with type 2 diabetes found that hyperuricemia was positively associated with central fat distribution, particularly VAT as measured by DXA [18]. Another study of 199 participants with polycystic ovary syndrome (PCOS) reported that a higher VAT mass, compared to values below 819.50 g, was linked to an increased risk of hyperuricemia [19]. While these studies focused on specific populations (diabetes and PCOS patients), our research broadened the scope by including a more representative sample of the general U.S. population. Moreover, our sample size was significantly larger, which enhances the robustness of our findings. We also employed RCS and subgroup analyses to explore the relationship between VAT area and SUA concentrations, adding methodological depth not present in the earlier studies. In a separate cross-sectional study with 371 participants, VAT was measured using magnetic resonance imaging, and SUA was found to be strongly associated with increased VAT [29]. However, this study treated SUA as the independent variable rather than the outcome, contrasting with our approach.

Some of the other previous research has predominantly focused on the association between SUA and other anthropometric measures. For example, a study of 174,698 adults undergoing routine physical exams found that the lipid accumulation product (LAP) index and cardiometabolic index (CMI) were more strongly correlated with hyperuricemia than other indices [30]. Similarly, a cross-sectional study involving 687 patients with type 2 diabetes demonstrated that the triglyceride-glucose index (TyG), TyG with BMI, the triglycerides to high-density lipoprotein cholesterol ratio (TG/HDL-c), and the metabolic score for insulin resistance (METS-IR) were positively associated with SUA levels [31]. Unlike these studies, which relied on calculated indices to assess insulin resistance, we utilized VAT measurements obtained through DXA. This method provides a more precise assessment of fat distribution compared to indirect indices such as TyG or METS-IR. The use of DXA minimizes variability associated with self-reported data or estimates, thereby yielding more reliable results. Another study of 23,715 adults from NHANES (1999–2018) found a positive relationship between total body fat percentage and SUA [32]. In contrast, our study specifically focused on VAT rather than total body fat, allowing us to minimize the influence of subcutaneous fat, which may not be as relevant to SUA levels. By isolating the impact of visceral fat, we offer a more nuanced understanding of the association with SUA.

Some biological mechanisms may explain the relationship between VAT and SUA. VAT accumulation can lead to elevated SUA levels by enhancing the expression of xanthine oxidoreductase in adipose tissue. This enzymatic activity promotes the increased production of uric acid, contributing to higher SUA concentrations [33]. Moreover, visceral fat accumulation results in decreased adiponectin levels, which contributes to the upregulation of pro-inflammatory mediators, including interleukin-6 and tumor necrosis factor-alpha [34]. This inflammatory state promotes enhanced purine metabolism and elevates SUA concentrations.

Our study presents several strengths. First, the use of the extensive NHANES database allowed us to achieve a large, representative sample, enhancing both the reliability and generalizability of our findings. Second, we applied rigorous statistical methods to examine the relationship between VAT and SUA levels, including analysis of a threshold effect, which provides a deeper understanding of this association. Third, our findings in specific subgroups—especially among females and younger individuals under 40 years—yield insights that can inform targeted public health interventions and further our understanding of demographic influences on metabolic health. Finally, the identification of a saturation point in the relationship between VAT and SUA highlights critical clinical implications, suggesting that interventions to manage SUA levels may need to be tailored according to visceral fat levels.

However, certain limitations must be acknowledged. First, the cross-sectional design limits our ability to establish causal relationships between VAT and SUA levels, making it challenging to determine temporal dynamics. To overcome this limitation, novel developed research methods will be necessary for future studies [35]. Second, reliance on self-reported data for some variables may introduce measurement bias, potentially affecting the accuracy of certain associations. Nevertheless, self-reported data remains a practical approach in large-scale epidemiological studies such as NHANES. Third, although the NHANES dataset is comprehensive, its findings may not be fully generalizable to populations outside the United States, which could limit the applicability of our conclusions across diverse demographic settings. Last, the exclusion of older adults may limit the generalizability of our findings to elderly populations. However, DXA data in the NHANES dataset were only available for participants aged 8–59 years.

Conclusions

This study found a positive association between VAT area and SUA levels in U.S. adults, with a stronger relationship observed when the VAT area was below 3.3 SDs. Additionally, age and sex were significant factors influencing this association, indicating a complex interaction between VAT and SUA across different demographic groups. These findings suggest potential physiological differences among subpopulations, which may have implications for targeted health interventions. The insights from this research provide a foundation for future longitudinal and mechanistic studies aimed at validating these results and exploring the underlying causal mechanisms in greater depth.

Data availability

The datasets generated during and analyzed during the current study are available in the NHANES repository, https://www.cdc.gov/nchs/nhanes/index.html.

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Acknowledgements

We gratefully thank Jie Liu of the Department of Vascular and Endovascular Surgery, Chinese PLA General Hospital for his contribution to the statistical support, study design consultations, and comments regarding the manuscript.Thanks to Zhang Jing (Second Department of Infectious Disease, Shanghai Fifth People’s Hospital, Fudan University) for his work on the NHANES database. His outstanding work, the nhanesR package, and webpage, make it easier for us to explore the NHANES database.

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  1. Xi Gu, Ping Gao, Ying Shen these three authors contributed equally to this work.

Authors and Affiliations

  1. Department of Endocrinology, RuiJin Hospital Lu Wan Branch, Shanghai Jiaotong University School of Medicine, No.149 Chongqing South Road, Shanghai, China

    Xi Gu, Ping Gao, Ying Shen & Leiqun Lu

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Contributions

X.G. wrote the original draft, conducted formal analysis, curated data, developed the methodology, and contributed to conceptualization. P.G. was responsible for data curation. Y.S. provided essential resources. L.L. supervised the study and validated the results. All authors reviewed and edited the manuscript.

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Correspondence to Leiqun Lu.

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Ethics approval and consent to participate

Approval was obtained from the NCHS Research Ethics Review Board. The procedures used in this study adhere to the tenets of the Declaration of Helsinki.

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Informed consent was obtained from all individual participants included in the study.

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The authors declare no competing interests.

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Gu, X., Gao, P., Shen, Y. et al. Non-linear association between visceral adipose tissue area and serum uric acid concentration in US adults: findings from NHANES 2011–2018. BMC Public Health 25, 1405 (2025). https://doi.org/10.1186/s12889-025-22557-y

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  • Published:

  • DOI: https://doi.org/10.1186/s12889-025-22557-y

Keywords

BMC Public Health

ISSN: 1471-2458

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