Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2024 Jun 21:15:1398917.
doi: 10.3389/fendo.2024.1398917. eCollection 2024.

Pro-inflammatory diets promote the formation of hyperuricemia

Affiliations

Pro-inflammatory diets promote the formation of hyperuricemia

Xin Liu et al. Front Endocrinol (Lausanne). .

Abstract

Background: Hyperuricemia, as a very prevalent chronic metabolic disease with increasing prevalence year by year, poses a significant burden on individual patients as well as on the global health care and disease burden, and there is growing evidence that it is associated with other underlying diseases such as hypertension and cardiovascular disease. The association between hyperuricemia and dietary inflammatory index (DII) scores was investigated in this study.

Methods: This study enrolled 13, 040 adult subjects (aged ≥ 20 years) from the US National Health and Nutrition Survey from 2003 to 2018. The inflammatory potential of the diet was assessed by the DII score, and logistic regression was performed to evaluate the relationship between the DII score and the development of hyperuricemia; subgroup analyses were used to discuss the influence of other factors on the relationship.

Results: Participants in the other quartiles had an increased risk of hyperuricemia compared to those in the lowest quartile of DII scores. Stratification analyses stratified by body mass index (BMI), sex, hypertension, drinking, diabetes, education level and albumin-creatinine-ratio (ACR) revealed that the DII score was also associated with the risk of hyperuricemia (P<0.05). There was an interaction in subgroup analysis stratified by sex, age, and hypertension (P for interaction <0.05). The results showed a linear-like relationship between DII and hyperuricemia, with a relatively low risk of developing hyperuricemia at lower DII scores and an increased risk of developing hyperuricemia as DII scores increased.

Conclusions: This study showed that the risk of hyperuricemia increased at slightly higher DII scores (i.e., with pro-inflammatory diets), but not significantly at lower levels (i.e., with anti-inflammatory diets). The contribution of the DII score to the development of hyperuricemia increased with higher scores. The relationship between inflammatory diets and hyperuricemia requires more research on inflammation, and this study alerts the public that pro-inflammatory diets may increase the risk of developing hyperuricemia.

Keywords: NHANES; diabetes; dietary inflammatory index; drinking; hypertension; hyperuricemia.

PubMed Disclaimer

Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Flow chart for study participant’s selection.
Figure 2
Figure 2
Associations between hyperuricemia and DII stratified by gender. CI, confidence interval; DII, Dietary Inflammatory Index, OR odds ratio. Model I: Unadjusted; Model II: Adjusted for age, race, BMI; Model III: Adjusted for family PIR, education level, BMI, drinking, smoking, cotinine, ALT, AST, BUN, GGT, LDH, diabetes, hypertension, and ACR in addition to Model II.
Figure 3
Figure 3
Associations between hyperuricemia and DII stratified by BMI. CI, confidence interval; DII, Dietary Inflammatory Index, OR odds ratio. Model I: Unadjusted; Model II: Adjusted for age, race, and sex; Model III: Adjusted for family PIR, education level, drinking, smoking, cotinine, ALT, AST, BUN, GGT, LDH, diabetes, hypertension, and ACR in addition to Model II.
Figure 4
Figure 4
Associations between hyperuricemia and DII stratified by hypertension. CI, confidence interval; DII, Dietary Inflammatory Index, OR odds ratio. Model I: Unadjusted; Model II: Adjusted for age, race, and sex; Model III: Adjusted for family PIR, education level, BMI, drinking, smoking, cotinine, ALT, AST, BUN, GGT, LDH, diabetes, and ACR, in addition to Model II.
Figure 5
Figure 5
Associations between hyperuricemia and DII stratified by drinking. CI, confidence interval; DII, Dietary Inflammatory Index, OR odds ratio. Model I: Unadjusted; Model II: Adjusted for age, race, and sex; Model III: Adjusted for family PIR, education level, BMI, smoking, cotinine, ALT, AST, BUN, GGT, LDH, diabetes, hypertension, and ACR in addition to Model II.
Figure 6
Figure 6
Associations between hyperuricemia and DII stratified by diabetes. CI, confidence interval; DII, Dietary Inflammatory Index, OR odds ratio. Model I: Unadjusted; Model II: Adjusted for age, race, and sex; Model III: Adjusted for family PIR, education level, BMI, drinking, smoking, cotinine, ALT, AST, BUN, GGT, LDH, hypertension, and ACR in addition to Model II.
Figure 7
Figure 7
Associations between hyperuricemia and DII stratified by education level. CI, confidence interval; DII, Dietary Inflammatory Index, OR odds ratio. Model I: Unadjusted; Model II: Adjusted for age, race, and sex; Model III: Adjusted for family PIR, BMI, drinking, smoking, cotinine, ALT, AST, BUN, GGT, LDH, hypertension, and ACR in addition to Model II.
Figure 8
Figure 8
Associations between hyperuricemia and DII stratified by albumin creatinine ratio. CI, confidence interval; DII: Dietary Inflammatory Index, OR odds ratio. Model I: Unadjusted; Model II: Adjusted for age, race, and sex; Model III: Adjusted for family PIR, education level, BMI, drinking, smoking, cotinine, ALT, AST, BUN, GGT, LDH and hypertension in addition to Model II.
Figure 9
Figure 9
Smooth curve fittings of DII and hyperuricemia. The red curve represents the relationship between DII and hyperuricemia, and the area between the blue dashed lines represents the 95% confidence interval obtained from the fit.

Similar articles

Cited by

References

    1. El Ridi R, Tallima H. Physiological functions and pathogenic potential of uric acid: A review. J Adv Res. (2017) 8:487–93. doi: 10.1016/j.jare.2017.03.003 - DOI - PMC - PubMed
    1. Badve SV, Brown F, Hawley CM, Johnson DW, Kanellis J, Rangan GK, et al. . Challenges of conducting a trial of uric-acid-lowering therapy in CKD. Nat Rev Nephrol. (2011) 7:295–300. doi: 10.1038/nrneph.2010.186 - DOI - PubMed
    1. Jalal DI, Chonchol M, Chen W, Targher G. Uric acid as a target of therapy in CKD. Am J Kidney Dis. (2013) 61:134–46. doi: 10.1053/j.ajkd.2012.07.021 - DOI - PMC - PubMed
    1. Li C, Hsieh MC, Chang SJ. Metabolic syndrome, diabetes, and hyperuricemia. Curr Opin Rheumatol. (2013) 25:210–6. doi: 10.1097/BOR.0b013e32835d951e - DOI - PubMed
    1. Grayson PC, Kim SY, LaValley M, Choi HK. Hyperuricemia and incident hypertension: a systematic review and meta-analysis. Arthritis Care Res (Hoboken). (2011) 63:102–10. doi: 10.1002/acr.20344 - DOI - PMC - PubMed

LinkOut - more resources