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Socioeconomic differences in hyperuricemia and gout: a systematic review and meta-analysis

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Abstract

Purpose

There are multiple risk factors have different influence on the disorder. However, the risk of hyperuricemia and gout in different socioeconomic status (SES) remains unclear. Recent studies provided results that contradicted to former studies. We aimed to perform a systematic review and meta-analysis of evidence to date and to assess the associations between SES and hyperuricemia or gout worldwide.

Methods

We searched MEDLINE, EMBASE, and Web of Science databases to identify studies that investigated the association between SES and hyperuricemia or gout. Studies that presented risk estimates were included. We conducted meta-analyses using random effects to combine unadjusted and adjusted effect estimates.

Results

Data from 14 studies were included, 9 provided data about hyperuricemia and 5 provided gout. Overall, there was an association between higher educational level and a higher risk of hyperuricemia (POR = 1.38, 95% CI 1.04–1.73) but lower risk of gout (POR = 0.59, 95% CI 0.47–0.71). Subgroup meta-analysis showed no association between all SES measures and hyperuricemia or gout in males or females.

Conclusions

Our study suggested that the associations between SES and hyperuricemia gout are different. Higher educational level was related to a higher risk of hyperuricemia but lower risk of gout. Given the limitations of our study, future studies are needed to investigate specific mechanisms underlying the relationship among SES differences in hyperuricemia and gout. Strategies to prevent and control SES inequalities in hyperuricemia and gout should be explored and adopted.

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Data availability

This is a systematic review of the literature, all the data presented are available and cited in the references section.

References

  1. N. Dalbeth, T.R. Merriman, L.K. Stamp, Gout. Lancet 388, 2039 (2016)

    Article  CAS  PubMed  Google Scholar 

  2. C.-F. Kuo, M.J. Grainge, W. Zhang, M. Doherty, Global epidemiology of gout: prevalence, incidence and risk factors. Nat. Rev. Rheumatol. 11, 649 (2015)

    Article  PubMed  Google Scholar 

  3. T. Bardin, P. Richette, Impact of comorbidities on gout and hyperuricaemia: an update on prevalence and treatment options. BMC Med. 15, 123 2017)

    Article  PubMed  PubMed Central  Google Scholar 

  4. A.E. Hak, G.C. Curhan, F. Grodstein, H.K. Choi, Menopause, postmenopausal hormone use and risk of incident gout. Ann. Rheum. Dis. 69, 1305–1309 (2010). https://doi.org/10.1136/ard.2009.109884

    Article  PubMed  Google Scholar 

  5. P.C. Robinson, Gout—an update of aetiology, genetics, co-morbidities and management. Maturitas 118, 67 (2018)

    Article  CAS  PubMed  Google Scholar 

  6. C.J. Smyth, C.W. Cotterman, R.H. Freyberg, The genetics of gout and hyperuricemie—an analysis of nineteen familes. J. Clin. Investig. 27, 749–759 (1948). https://doi.org/10.1172/JCI102025

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. S.W. Lai, C.K. Tan, K.C. Ng, Epidemiology of hyperuricemia in the elderly. Yale J. Biol. Med. 74, 151–157 (2001)

    CAS  PubMed  PubMed Central  Google Scholar 

  8. R. Villegas, Y.-B. Xiang, Q. Cai, S. Fazio, M. Linton, H. Li, T. Elasy, W. Zheng, X.O. Shu, Prevalence and determinants of hyperuricemia in middle-aged, Urban Chinese men. Metab. Syndr. Relat. Disord. 8, 263–270 (2010). https://doi.org/10.1089/met.2009.0084

    Article  PubMed  PubMed Central  Google Scholar 

  9. M.A. McAdams-Demarco, A. Law, J.W. Maynard, J. Coresh, A.N. Baer, Risk factors for incident hyperuricemia during mid-adulthood in African American and White men and women enrolled in the ARIC cohort study. BMC Musculoskelet. Disord. 14 (2013). https://doi.org/10.1186/1471-2474-14-347

  10. Y.L. Qu, L. Yu, Z.M. Li, L.H. Kong, T.C. Xiao, M. Li, N.N. Luo, X.F. Deng, K.Y. Qu, Epidemiological status and risk factors of hyperuricemia in rural area of the Three Gorges. Chin. J. Cardiol. 41, 427–431 (2013). https://doi.org/10.3760/cma.j.issn.0253-3758.2013.05.015

    Article  Google Scholar 

  11. L. Liu, S. Lou, K. Xu, Z. Meng, Q. Zhang, K. Song, Relationship between lifestyle choices and hyperuricemia in Chinese men and women. Clin. Rheumatol. 32, 233–239 (2013). https://doi.org/10.1007/s10067-012-2108-z

    Article  PubMed  Google Scholar 

  12. P. Song, H. Wang, W. Xia, X. Chang, M. Wang, L. An, Prevalence and correlates of hyperuricemia in the middle-aged and older adults in China. Sci. Rep. 8, 4314 2018). https://doi.org/10.1038/s41598-018-22570-9

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Y. Kim, J. Kang, G.T. Kim, Prevalence of hyperuricemia and its associated factors in the general Korean population: an analysis of a population-based nationally representative sample. Clin. Rheumatol. 37, 2529–2538 (2018). https://doi.org/10.1007/s10067-018-4130-2

    Article  PubMed  Google Scholar 

  14. Y. Shen, Y. Wang, C. Chang, S. Li, W. Li, B. Ni, Prevalence and risk factors associated with hyperuricemia among working population at high altitudes: a cross-sectional study in Western China. Clin. Rheumatol. 38, 1375–1384 (2019). https://doi.org/10.1007/s10067-018-4391-9

    Article  PubMed  Google Scholar 

  15. D.F. Stroup, J.A. Berlin, S.C. Morton, I. Olkin, G.D. Williamson, D. Rennie, D. Moher, B.J. Becker, T.A. Sipe, S.B. Thacker,and for the M.O.O.S. in E. Group, Meta-analysis of observational studies in epidemiology: a proposal for reporting. JAMA 283, 2008 (2000). https://doi.org/10.1001/jama.283.15.2008

    Article  CAS  PubMed  Google Scholar 

  16. J.P. Vandenbroucke, E. von Elm, D.G. Altman, P.C. Gotzsche, C.D. Mulrow, S.J. Pocock, C. Poole, J.J. Schlesselman, M. Egger, Strengthening the Reporting of Observational Studies in Epidemiology (STROBE): explanation and elaboration. PLoS Med. 4, e297 (2007). https://doi.org/10.1371/journal.pmed.0040297

    Article  PubMed  PubMed Central  Google Scholar 

  17. S. Sanderson, I.D. Tatt, J.P.T. Higgins, Tools for assessing quality and susceptibility to bias in observational studies in epidemiology: a systematic review and annotated bibliography. Int. J. Epidemiol. 36, 666–676 (2007). https://doi.org/10.1093/ije/dym018

    Article  PubMed  Google Scholar 

  18. R. DerSimonian, N. Laird, Meta-analysis in clinical trials. Control. Clin. Trials 7, 177–188 (1986)

    Article  CAS  PubMed  Google Scholar 

  19. J.P. Higgins, Cochrane handbook for systematic reviews of interventions. Version 5.1. 0 [updated March 2011]. The Cochrane Collaboration (2011). www.training.cochrane.org/handbook

  20. J.A. Sterne, M. Egger, Funnel plots for detecting bias in meta-analysis: guidelines on choice of axis. J. Clin. Epidemiol. 54, 1046–1055 (2001). https://doi.org/10.1016/s0895-4356(01)00377-8

    Article  CAS  PubMed  Google Scholar 

  21. G.Schwarzer, Meta: an R package for meta-analysis. R News 7, 40–45 (2007)

    Google Scholar 

  22. V. Bhole, M. de Vera, M.M. Rahman, E. Krishnan, H. Choi, Epidemiology of gout in women: fifty-two-year followup of a prospective cohort. Arthritis Rheum. 62, 1069–1076 (2010). https://doi.org/10.1002/art.27338

    Article  PubMed  Google Scholar 

  23. R.A. Hayward, T. Rathod, E. Roddy, S. Muller, S.L. Hider, C.D. Mallen, The association of gout with socioeconomic status in primary care: a cross-sectional observational study. Rheumatology 52, 2004–2008 (2013). https://doi.org/10.1093/rheumatology/ket262

    Article  PubMed  PubMed Central  Google Scholar 

  24. H. Liu, X.M. Zhang, Y.L. Wang, B.C. Liu, Prevalence of hyperuricemia among Chinese adults: a national cross-sectional survey using multistage, stratified sampling. J. Nephrol. 27, 653–658 (2014). https://doi.org/10.1007/s40620-014-0082-z

    Article  CAS  PubMed  Google Scholar 

  25. P. Wandell, A.C. Carlsson, X. Li, D. Gasevic, J. Arnlov, M.J. Holzmann, J. Sundquist, K. Sundquist, Gout in immigrant groups: a cohort study in Sweden. Clin. Rheumatol. 36, 1091–1102 (2017). https://doi.org/10.1007/s10067-016-3525-1

    Article  PubMed  PubMed Central  Google Scholar 

  26. W.G. Fang, X.M. Huang, Y. Wang, W.G. Zhu, Z.X. Bie, J.L. Chen, X.J. Zeng, A cross-sectional study of hyperuricemia in state-employees in Beijing: prevalence and risk factors.Natl Med. J. China 86, 1764–1768 (2006)

    CAS  Google Scholar 

  27. M. Uetani, Y. Suwazono, E. Kobayashi, T. Inaba, M. Oishi, K. Nogawa, A longitudinal study of the influence of shift work on serum uric acid levels in workers at a telecommunications company. Occup. Med. 56, 83–88 (2006). https://doi.org/10.1093/occmed/kqi178

    Article  Google Scholar 

  28. L. Winters-Miner, Personalized Medicine. In: L. Winters-Miner, P.S. Bolding, et al. (eds), Practical Predictive Analytics and Decisioning Systems for Medicine, pp 176–204. Academic Press (2015)

  29. M.M. Ibrahim, A. Damasceno, Hypertension in developing countries. Lancet 380, 611–619 (2012). https://doi.org/10.1016/S0140-6736(12)60861-7

    Article  PubMed  Google Scholar 

  30. J. Schmidhuber, P. Shetty, The nutrition transition to 2030. Why developing countries are likely to bear the major burden. Food Econ. Acta Agric. Scand. Sect. C 2, 150–166 (2005). https://doi.org/10.1080/16507540500534812

    Article  Google Scholar 

  31. T. Bärnighausen, D.E. Bloom, S. Humair, 3—Global health governance and tropical diseases. Presented at the (2014)

  32. S.C. Larsson, S. Burgess, K. Michaëlsson, Genetic association between adiposity and gout: a Mendelian randomization study. Rheumatology 57, 2145–2148 (2018). https://doi.org/10.1093/rheumatology/key229

    Article  CAS  PubMed  Google Scholar 

  33. S.C. Larsson, M. Carlström, Coffee consumption and gout: a Mendelian randomisation study. Ann. Rheum. Dis., 4–6 (2018). https://doi.org/10.1136/annrheumdis-2018-213055

  34. T.J. Major, N. Dalbeth, E.A. Stahl, T.R. Merriman, An update on the genetics of hyperuricaemia and gout. Nat. Rev. Rheumatol. 14, 351–353 (2018). https://doi.org/10.1038/s41584-018-0004-x

    Article  CAS  Google Scholar 

  35. G.D. Smith, M. Egger, Meta-analyses of observational data should be done with due care. BMJ 318, 56 (1999)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. I. Shrier, J.-F. Boivin, R.J. Steele, R.W. Platt, A. Furlan, R. Kakuma, J. Brophy, M. Rossignol, Should meta-analyses of interventions include observational studies in addition to randomized controlled trials? Acritical examination of underlying principles. Am. J. Epidemiol. 166, 1203–1209 (2007). https://doi.org/10.1093/aje/kwm189

    Article  PubMed  Google Scholar 

  37. B. Galobardes, M. Shaw, D.A. Lawlor, J.W. Lynch, G. Davey Smith, Indicators of socioeconomic position (part 1). J. Epidemiol. Community Health 60, 7–12 (2006). https://doi.org/10.1136/jech.2004.023531

    Article  PubMed  PubMed Central  Google Scholar 

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Authors and Affiliations

  1. The First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, 511436, PR China

    Zhe Pan, Mingkai Huang, Ming Fang, Xu Xie & Ze Huang

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Pan, Z., Huang, M., Fang, M. et al. Socioeconomic differences in hyperuricemia and gout: a systematic review and meta-analysis. Endocrine 69, 286–293 (2020). https://doi.org/10.1007/s12020-020-02281-w

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