Skip to main content
×
×
Home

A dietary pattern rich in animal organ, seafood and processed meat products is associated with newly diagnosed hyperuricaemia in Chinese adults: a propensity score-matched case–control study

  • Yang Xia (a1) (a2), Qi Xiang (a3), Yeqing Gu (a1), Suwei Jia (a4), Qing Zhang (a2), Li Liu (a2), Ge Meng (a1), Hongmei Wu (a1), Xue Bao (a1), Bin Yu (a1), Shaomei Sun (a2), Xing Wang (a2), Ming Zhou (a2), Qiyu Jia (a2), Yuntang Wu (a1), Kun Song (a2) and Kaijun Niu (a1) (a2)...
Abstract

Previous studies have indicated that some food items and nutrients are associated with uric acid metabolism in humans. However, little is known about the role of dietary patterns in hyperuricaemia. We designed this case–control study to evaluate the associations between dietary patterns and newly diagnosed hyperuricaemia in Chinese adults. A total of 1422 cases and 1422 controls were generated from 14 538 participants using the 1:1 ratio propensity score matching methods. Dietary intake was assessed using a validated self-administered FFQ. Dietary patterns were derived by factor analysis. Hyperuricaemia was defined as concentrations of serum uric acid higher than 7 mg/dl (416·5 μmol/l) for men and 6 mg/dl (357 μmol/l) for women. Three dietary patterns were derived by factor analysis: sweet pattern; vegetable pattern; animal foods pattern. The animal foods pattern characterised by higher intake of an animal organ, seafood and processed meat products was associated with higher prevalence of newly diagnosed hyperuricaemia (P for trend<0·01) after adjustment. Compared with the participants in the lowest quartile of the animal foods pattern, the OR of newly diagnosed hyperuricaemia in the highest quartile was 1·50 (95 % CI 1·20, 1·87). The other two dietary patterns were not associated with the prevalence of newly diagnosed hyperuricaemia after adjustment. In conclusion, a diet rich in animal organ, seafood and processed meat products is associated with higher prevalence of newly diagnosed hyperuricaemia in a Chinese population. Further cohort studies and randomised controlled trials are required to clarify these findings.

Copyright
Corresponding author
* Corresponding author: K. Niu, email nkj0809@gmail.com; niukaijun@tmu.edu.cn
Footnotes
Hide All

These authors contributed equally to this work.

Footnotes
References
Hide All
1. Choi, HK (2010) A prescription for lifestyle change in patients with hyperuricemia and gout. Curr Opin Rheumatol 22, 165172.
2. B, L, T, W, Hn, Z, et al. (2011) The prevalence of hyperuricemia in China: a meta-analysis. BMC Public Health 11, 832.
3. Doghramji, PP & Wortmann, RL (2012) Hyperuricemia and gout: new concepts in diagnosis and management. Postgrad Med 124, 98109.
4. Billiet, L, Doaty, S, Katz, JD, et al. (2014) Review of hyperuricemia as new marker for metabolic syndrome. ISRN Rheumatol 2014, 852954.
5. Borghi, C, Verardi, FM, Pareo, I, et al. (2014) Hyperuricemia and cardiovascular disease risk. Expert Rev Cardiovasc Ther 12, 12191225.
6. Isaka, Y, Takabatake, Y, Takahashi, A, et al. (2016) Hyperuricemia-induced inflammasome and kidney diseases. Nephrol Dial Transplant 31, 890896.
7. Liu, R, Han, C, Wu, D, et al. (2015) Prevalence of Hyperuricemia and Gout in Mainland China from 2000 to 2014: a systematic review and meta-analysis. Biomed Res Int 2015, 762820.
8. Zhu, Y, Pandya, BJ & Choi, HK (2011) Prevalence of gout and hyperuricemia in the US general population: the National Health and Nutrition Examination Survey 2007–2008. Arthritis Rheum 63, 31363141.
9. Roddy, E & Choi, HK (2014) Epidemiology of gout. Rheum Dis Clin North Am 40, 155175.
10. Choi, HK, Atkinson, K, Karlson, EW, et al. (2004) Purine-rich foods, dairy and protein intake, and the risk of gout in men. N Engl J Med 350, 10931103.
11. Choi, HK, Atkinson, K, Karlson, EW, et al. (2004) Alcohol intake and risk of incident gout in men: a prospective study. Lancet 363, 12771281.
12. Gao, X, Qi, L, Qiao, N, et al. (2007) Intake of added sugar and sugar-sweetened drink and serum uric acid concentration in US men and women. Hypertension 50, 306312.
13. Hu, FB (2002) Dietary pattern analysis: a new direction in nutritional epidemiology. Curr Opin Lipidol 13, 39.
14. Guasch-Ferre, M, Bullo, M, Babio, N, et al. (2013) Mediterranean diet and risk of hyperuricemia in elderly participants at high cardiovascular risk. J Gerontol A Biol Sci Med Sci 68, 12631270.
15. Zhang, M, Chang, H, Gao, Y, et al. (2012) Major dietary patterns and risk of asymptomatic hyperuricemia in Chinese adults. J Nutr Sci Vitaminol (Tokyo) 58, 339345.
16. Tsai, YT, Liu, JP, Tu, YK, et al. (2012) Relationship between dietary patterns and serum uric acid concentrations among ethnic Chinese adults in Taiwan. Asia Pac J Clin Nutr 21, 263270.
17. Song, K, Du, H, Zhang, Q, et al. (2014) Serum immunoglobulin M concentration is positively related to metabolic syndrome in an adult population: Tianjin Chronic Low-Grade Systemic Inflammation and Health (TCLSIH) Cohort Study. PLOS ONE 9, e88701.
18. Austin, PC (2011) An introduction to propensity score methods for reducing the effects of confounding in observational studies. Multivariate Behav Res 46, 399424.
19. Jia, Q, Xia, Y, Zhang, Q, et al. (2015) Dietary patterns are associated with prevalence of fatty liver disease in adults. Eur J Clin Nutr 69, 914921.
20. Yang, YX, Wang, GY, Pan, XC, et al. (2009) China Food Composition, 2nd ed. Beijing: Peking University Medical Press.
21. Zhang, W, Doherty, M, Pascual, E, et al. (2006) EULAR evidence based recommendations for gout. Part I: Diagnosis. Report of a task force of the Standing Committee for International Clinical Studies Including Therapeutics (ESCISIT). Ann Rheum Dis 65, 13011311.
22. Alberti, KG, Eckel, RH, Grundy, SM, et al. (2009) Harmonizing the metabolic syndrome: a joint interim statement of the International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; and International Association for the Study of Obesity. Circulation 120, 16401645.
23. Craig, CL, Marshall, AL, Sjostrom, M, et al. (2003) International physical activity questionnaire: 12-country reliability and validity. Med Sci Sports Exerc 35, 13811395.
24. McNeish, D (2017) Exploratory factor analysis with small samples and missing data. J Pers Assess 99, 637652.
25. Schlesinger, N (2005) Dietary factors and hyperuricaemia. Curr Pharm Des 11, 41334138.
26. Ryu, KA, Kang, HH, Kim, SY, et al. (2014) Comparison of nutrient intake and diet quality between hyperuricemia subjects and controls in Korea. Clin Nutr Res 3, 5663.
27. Nakagawa, T, Tuttle, KR, Short, RA, et al. (2005) Hypothesis: fructose-induced hyperuricemia as a causal mechanism for the epidemic of the metabolic syndrome. Nat Clin Pract Nephrol 1, 8086.
28. Choi, HK & Curhan, G (2008) Soft drinks, fructose consumption, and the risk of gout in men: prospective cohort study. BMJ 336, 309312.
29. Nguyen, S, Choi, HK, Lustig, RH, et al. (2009) Sugar-sweetened beverages, serum uric acid, and blood pressure in adolescents. J Pediatr 154, 807813.
30. Chuang, SY, Lee, SC, Hsieh, YT, et al. (2011) Trends in hyperuricemia and gout prevalence: Nutrition and Health Survey in Taiwan from 1993–1996 to 2005–2008. Asia Pac J Clin Nutr 20, 301308.
31. D’Agostino, RB Jr (1998) Propensity score methods for bias reduction in the comparison of a treatment to a non-randomized control group. Stat Med 17, 22652281.
Recommend this journal

Email your librarian or administrator to recommend adding this journal to your organisation's collection.

British Journal of Nutrition
  • ISSN: 0007-1145
  • EISSN: 1475-2662
  • URL: /core/journals/british-journal-of-nutrition
Please enter your name
Please enter a valid email address
Who would you like to send this to? *
×

Keywords

" class="button small radius grey keywords">
physical activity

Metrics

Full text views

Total number of HTML views: 5
Total number of PDF views: 60 *
Loading metrics...

Abstract views

Total abstract views: 227 *
Loading metrics...

* Views captured on Cambridge Core between 15th May 2018 - 20th August 2018. This data will be updated every 24 hours.