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. 2020 Nov 30;5:52. doi: 10.1186/s41256-020-00178-9

Geographical distribution of hyperuricemia in mainland China: a comprehensive systematic review and meta-analysis

Jiayun Huang 1,#, Zheng Feei Ma 1,2,✉,#, Yutong Zhang 3, Zhongxiao Wan 4, Yeshan Li 5, Hang Zhou 6,7, Anna Chu 8, Yeong Yeh Lee 2,9,10
PMCID: PMC7708223  PMID: 33292806

Abstract

Background

Fructose plays an important role in the complex metabolism of uric acid in the human body. However, high blood uric acid concentration, known as hyperuricemia, is the main risk factor for development of gout. Therefore, we conducted an updated meta-analysis on the prevalence and geographical distribution of hyperuricemia among the general population in mainland China using systematic literature search.

Methods

Five electronic databases were used to search for relevant articles published until 2019. All calculations were conducted using the Comprehensive Meta-Analysis (CMA) software. We included 108 eligible articles (172 studies by sex, 95 studies by regions, and 107 studies by study type) and an overall sample size of > 808,505 participants.

Results

The pooled prevalence of hyperuricemia among the general population in mainland China was 17.4% (95% CI: 15.8–19.1%). Our subgroup analysis indicated that the pooled prevalence by regions ranged from 15.5 to 24.6%. Those living Northeast region and being males had the highest prevalence (P < 0.001). In addition, some provinces in South Central, East and Northeast regions reported a high prevalence (> 20%), particularly in males. An increasing prevalence was reported since 2005–2009 until 2015–2019. No publication of bias was observed as indicated by a symmetrical funnel plot and Begg and Mazumdar rank correlation (P = 0.392).

Conclusion

Prevalence of hyperuricemia is increasing in China, and future studies should investigate the association between the prevalence of hyperuricemia and its risk factors in order to tackle the issue, particularly among the vulnerable groups. Also, our study was the first comprehensive study to investigate the overall prevalence of hyperuricemia in mainland China covering the six different regions.

Keywords: Uric acid, Hyperuricemia, Gout, China, Urbanisation

Background

High blood uric acid concentration, known as hyperuricemia, is the main risk factor for development of gout [1, 2]. Uric acid is a terminal metabolite of human purine compounds, which is slightly soluble in water and easy to form crystals [3, 4]. When uric acid increases to a certain threshold level in the human body, it is considered hyperuricemia [5].

The body has ~ 1200 mg and ~ 600 mg total body pool of exchangeable uric acid in males and females, respectively [6]. There are about 600 mg uric acid that are produced every day, and another 600 mg uric acid are excreted, resulting in a balanced state [7]. A disturbed state of purine metabolism can cause a variety of disorders, such as hyperuricemia, chronic gout, joint deformation and renal failure [3]. Among them, hyperuricemia has received increasing attention in recent decades because of its increasing global trends and risk of associated metabolic diseases. The prevalence of hyperuricemia can be influenced by several factors, including genetics, gender, age, lifestyle, diet, medication and economic development. For example, a higher prevalence is usually reported in the economically developed regions [8].

In addition, higher uric acid concentration is associated with increased risk of hospitalization, chronic kidney disease and cardiovascular disease (CVD), which can result in higher total medical costs and hospitalisation costs per patient. For example, the mean annual healthcare costs in Italy for hyperuricemic patients ranged from €2752 to €4607 [5]. Elderly patients with hyperuricemia in China are at risk of gout attacks caused by iatric problems, which may bring about complications such as deep vein thrombosis (DVT) and a prolonged hospital stay [9]. Therefore, this does not only increase the cost of medical treatment for patients, but also increase the cost of treatment for hospitals.

There are many observational studies on the prevalence of hyperuricemia, however most of them were focused on specific populations such as children from a region of mainland China. In addition, there are only two meta-analyses in the past that have examined the prevalence of hyperuricemia in mainland China; both with limitations [10, 11]. The first meta-analysis was conducted in 2011 with 59 articles [10] and the second one was in 2015 with 44 articles [11]; both did not have comprehensive coverage of the whole of China (for example, the former one did not include Inner Mongolia, while the latter one did not include Ningxia and Qinghai). Since China is the world’s most populous country with about 1.4 billion (i.e. 18.4% of the world population), updating the epidemiology of hyperuricemia can help to fill the gap in public health research and policy. To date, there have been no published English articles that have extensively reviewed the prevalence of hyperuricemia in mainland China until December 2019. Therefore, the aim of our study was to conduct a comprehensive review and quantitative meta-analysis on the prevalence of hyperuricemia in mainland China over the past two decades. In addition, analyses were also performed to provide a more detailed and updated epidemiological distribution of hyperuricemia by comparing different regions in mainland China.

Methods

Search strategy

A systematic literature search from January 1995 to December 2019 was conducted for articles published in Chinese language from the following electronic databases: Wanfang Data, Shanghai Science and Technology Innovation Resources Center (SSTIR), China National Knowledge Infrastructure (CNKI) and Chinese Scientific Journals Fulltext Database (CQVIP). Keywords used in the database search included: “hyperuricemia” OR “high uric acid” OR “uric acid” OR “gout” AND “Chinese” OR “China” OR the name of the provinces in China. Database search results were entered into EndNote X8.2 file (Clarivate Analytics, New York, USA). The current systematic review and meta-analysis was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines [12] (Fig. 1). The protocol of the systematic review and meta-analysis was registered at PROSPERO, as CRD42019141243, which is an international database of prospectively registered systematic reviews in health and social care. Since our systematic review and meta-analysis used data from published articles, there are no requirements for us to apply for the ethics approval. However, all human studies included in our systematic review and meta-analysis have been reviewed by the appropriate ethics committee in their institutions and have therefore been performed in accordance with the ethical standards laid down in an appropriate version of the WMA Declaration of Helsinki-Ethical Principles for Medical Research Involving Human Subject.

Fig. 1.

Fig. 1

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PRISMA flow diagram of the literature screening process

Study selection

Studies were deemed to be eligible if they met the following criteria: (1) cross-sectional, cohort or case-control studies that were conducted in non-pregnant adults living in mainland China; (2) prevalence of hyperuricemia and sample size were reported; (3) detailed diagnostic criteria were included; and (4) full text of the article was able to be retrieved. Studies were excluded if they were: review articles and/or meta-analyses and inclusion of terminally ill or pregnant adults as participants.

Quality assessment

The quality of eligible studies was independently assessed by two authors (J. H. and Z. F. M.) using a modified version of Newcastle-Ottawa Scale (NOS). When there were disagreements between the authors, they were resolved by discussion.

Data extraction

For all eligible studies, the information about the authors, publication year, study design, age, sex, province, cases of hyperuricemia, total sample size, prevalence of hyperuricemia and cut-offs used for the determination of hyperuricemia was extracted. The corresponding authors of eligible studies were also contacted for obtaining the missing data in their articles.

Statistical analysis

Meta-analysis was performed using the Comprehensive Meta-Analysis (CMA) software (V2.0, Biostat, Englewood, New Jersey). Random-effects models were used to estimate the pooled prevalence of hyperuricemia and 95% confidence intervals (CI) due to the large variation of study design among the included studies. Subgroup analyses were performed by province, study design, sex and study period. Heterogeneity tests were determined using the Q-test (P < 0.10) and I2 statistic (> 75%) [13]. Potential publication bias was assessed by the funnel plots and Begg and Mazumdar rank correlation (P < 0.05). The one-study-removed sensitivity analysis was performed to determine the possible causes of heterogeneity between the studies.

Results

Characteristics of the included studies

A total of 108 articles were identified after screening for relevancy and duplicates (Fig. 1). Table 1 shows a detailed description of the included studies in the systematic review and meta-analysis [10–12, 14–123]. All included studies were published between 1999 and 2019 and together comprised > 808,505 participants. Of the 108 articles, there were 172 studies by sex, 95 studies by regions, and 107 studies by study type (Table 2).

Table 1.

Characteristics of the included studies in the systematic review and meta-analysis

No. Study Study type Provinces (cities)/municipalities/autonomous regions Region Age (years)c Case Sample size Prevalence (%) Diagnostic cut-offs Gender
1 Ma, Chen & Li (1999) [14] CS Guangdong South Central 55–82 452 2041 22.1 >420 μmol/L Both
364 1696 21.5 >420 μmol/L Male
88 345 25.5 >420 μmol/L Female
2 Shao et al. (2003) [15] CS Nanjing East ≥18 1038 7778 13.3 NS Both
688 3790 17.6 ≥417 μmol/L Male
370 3988 9.3 ≥357 μmol/L Female
3 Chen et al. (2004) [16] CC Anhui East 45 ± 12 105 430 24.4 NS Both
70 227 30.8 >420 μmol/L Male
35 203 17.2 >360 μmol/L Female
4 Wu et al. (2005) [17] CS Guangzhou, Guangdong South Central > 55 197 642 30.7 NS Both
46 152 30.3 >420 μmol/L Male
151 490 30.8 >350 μmol/L Female
5 Yang et al. (2005) [18] CS Shandong East 18–54 537 8640 6.2 NS Both
459 6289 7.3 ≥416 μmol/L Male
78 2351 3.3 ≥357 μmol/L Female
6 Wang et al. (2006) [19] CS Shandong East 20–80 269 2605 10.3 > 350 μmol/L Female
7 Li et al. (2008) [20] CH Chinaa NAa 45–54 10 274 3.6 NS Both
5 90 5.6 ≥416 μmol/L Male
5 184 2.7 ≥356 μmol/L Female
55–64 18 307 5.9 NS Both
13 138 9.4 ≥416 μmol/L Male
5 169 3.0 ≥356 μmol/L Female
65–74 21 229 9.2 NS Both
12 116 10.3 ≥416 μmol/L Male
9 113 8.0 ≥356 μmol/L Female
8 Fan et al. (2009) [118] CS Xinyang, Henan South Central 40–75 738 5235 14.1 NS Both
379 1763 21.5 ≥420 μmol/L Male
354 3472 10.2 ≥360 μmol/L Female
9 Lu et al. (2010) [21] CS Tianjin North 22–53 19 151 12.6 ≥410 μmol/L Male
10 Yu et al. (2010) [22] CS Foshan, Guangdong South Central 20–88 1117 7403 15.1 NS Both
714 3581 19.9 ≥417 μmol/L Male
403 3822 10.5 ≥357 μmol/L Female
11 Yuan et al. (2011) [23] CS Guiyang Southwest > 60 399 2600 15.3 ≥420 μmol/L Both
227 1430 15.9 NS Male
172 1170 14.7 NS Female
12 Zhang & Zhang (2011) [24] CS Chinaa NAa ≥18 427 5774 7.4 NS Both
13 Guo et al. (2012) [25] CS Taiyuan, Shanxi Northwest 23–87 371 4228 8.8 NS Both
249 1308 19.0 ≥420 μmol/L Male
122 2920 4.2 ≥420 μmol/L Female
14 Wang et al. (2012) [26] CS Yinchuan, Ningxia Northwest ≥18 926 5921 15.6 NS Both
1352 7322 18.5 NS Both
1635 8717 18.8 NS Both
15 Chen et al. (2013) [27] CS Guangxi South Central ≥18 319 927 34.4 NS Both
157 419 30.9 NS Male
162 508 38.7 NS Female
16 Duan et al. (2013) [28] CS Xinjiang Northwest ≥18 261 2046 12.8 NS Both
228 823 27.7 >417 μmol/L Male
33 1223 2.7 >357 μmol/L Female
17 Li et al. (2013) [29] CS Quanzhou, Fujian East 40–80 253 1358 18.6 NS Both
99 363 27.3 ≥416 μmol/L Male
154 995 15.5 ≥357 μmol/L Female
18 Li & Cao (2013) [30] CS Karamay, Xinjiang Northwest ≥18 310 2032 15.3 NS Both
268 1086 24.7 NS Male
42 946 4.4 NS Female
19 Lv et al. (2013) [31] CS Yantai, Shandong East 31–78 66 635 10.4 ≥380 μmol/L Both
20 Su et al. (2013) [32] CS Nanhai, Guangdong South Central 45–80 415 2015 20.6 NS Both
271 1110 24.4 >420 μmol/L Male
144 905 16.9 >357 μmol/L Female
21 Wang et al. (2013) [33] CS Shanghai East 40–70 58 1928 3.0 NS Both
33 582 5.7 >420 μmol/L Male
25 1346 1.9 >357 μmol/L Female
22 Zhang, Wu & Lv (2013) [34] CS Hebei North 21–95 693 3232 21.4 NS Both
446 1897 23.5 ≥428 μmol/L Male
247 1335 18.5 ≥357 μmol/L Female
23 Zhou & He (2013) [35] CH Shenyang, Liaoning Northeast 50–70 8 70 34.8 NS Both
24 Chen, Dai & Lin (2014) [36] CS Guangzhou, Guangdong South Central 45–75 603 1176 51.3 NS Both
341 612 55.7 >420 μmol/L Male
262 564 46.5 >357 μmol/L Female
25 Cui et al. (2014) [37] CS Hebei North ≥20 1091 7083 15.4 NS Both
904 5357 16.9 ≥417 μmol/L Male
187 1726 10.8 ≥357 μmol/L Female
26 Li, Zhao, Gao (2014) [38] CS Yunnan Southwest 27–89 367 2947 12.5 NS Both
303 1827 16.6 >420 μmol/L Male
64 1120 5.7 >360 μmol/L Female
27 Lin et al. (2014) [39] CS Guangdong South Central > 60 190 1036 18.3 NS Both
86 383 22.5 ≥420 μmol/L Male
104 653 15.9 ≥420 μmol/L Female
28 Liu et al. (2014) [40] CS Jilin Northeast 38 ± 10 3395 16,807 20.2 NS Both
2930 9736 30.1 NS Male
465 7071 6.6 NS Female
29 Pan et al. (2014) [41] CS Jiangsu East 35–70 573 3122 18.4 NS Both
362 1349 26.8 ≥420 μmol/L Male
211 1773 11.9 ≥380 μmol/L Female
30 Song et al. (2014) [42] CS Jiangxi East > 40 795 3795 20.9 NS Both
488 1824 26.8 >420 μmol/L Male
307 1971 15.6 >350 μmol/L Female
31 Yong & Ye (2014) [43] CS Hebei North ≥18–20 813 5269 15.4 NS Both
769 2717 28.3 >420 μmol/L Male
44 2552 1.7 >350 μmol/L Female
32 Zhu, Wang, Liu (2014) [44] CS Xinjiang Northwest 20–93 1489 10,025 14.9 NS Both
33 Cao, Li & Yi (2015) [45] CS Guangzhou, Guangdong South Central 20–80 290 988 29.4 NS Both
264 601 43.9 >420 μmol/L Male
26 387 6.7 >350 μmol/L Female
34 Li et al. (2015a) [46] CS Gansu Northwest 48 ± 15 392 2364 16.6 NS Both
256 1254 20.4 >420 μmol/L Male
136 1110 12.3 >360 μmol/L Female
35 Li et al. (2015b) [47] CS Guangxi South Central ≥20 14,181 51,206 27.7 NS Both
10,722 27,144 39.5 ≥417 μmol/L Male
3459 24,062 14.4 ≥357 μmol/L Female
36 Li et al. (2015c) [48] CS Dongguan, Guangdong South Central ≥18 519 1375 37.6 NS Both
366 657 26.6 >420 μmol/L Male
153 718 11.1 >350 μmol/L Female
37 Liu et al. (2015) [11] CS Guangzhou, Guangdong South Central ≥18 1334 4237 31.5 NS Both
859 2257 38.1 >420 μmol/L Male
475 1980 24.0 >360 μmol/L Female
38 Lu (2015) [49] CS Shanghai East 65–85 220 1128 19.5 NS Both
165 607 27.2 >420 μmol/L Male
63 511 12.3 >350 μmol/L Female
39 Zhao (2015) [50] CS Chinaa NAa 20–60 4616 12,650 36.5 NS Both
40 Zhou et al. (2015a) [51] CS Sichuan Southwest ≥18 182 972 18.7 NS Both
123 452 27.2 ≥420 μmol/L Male
59 520 11.3 ≥360 μmol/L Female
41 Zhou et al. (2015b) [52] CS Henan South Central 20–60 1196 4916 24.3 NS Both
1128 4290 26.3 ≥420 μmol/L Male
68 626 10.9 ≥357 μmol/L Female
42 Guli, He & Zhang (2016) [53] CS Gansu Northwest 20–80 780 6400 12.2 >420 μmol/L Both
43 Chen & Xing (2016) [54] CS Beijing North 25–82 151 868 17.4 ≥416 μmol/L Male
44 Chen & Zhou (2016) [55] CS Zhejiang East > 60 691 4160 16.6 NS Both
393 2182 18.0 >420 μmol/L Male
298 1978 15.1 >360 μmol/L Female
45 Fan et al. (2016) [56] CS Shanghai East ≥18 5413 27,615 19.6 NS Both
3993 14,104 28.3 >420 μmol/L Male
1420 13,511 10.5 >357 μmol/L Female
46 Feng et al. (2016) [57] CS Jiangsu East 18–93 219 1352 16.2 NS Both
129 609 21.2 >420 μmol/L Male
90 743 12.1 >350 μmol/L Female
47 Li (2016) [58] CS Tianjin North ≥18 10,344 77,787 13.3 NS Both
48 Li et al. (2016) [59] CS Chongqing Southwest 39 1596 26,067 6.1 NS Both
1272 18,139 7.0 ≥420 μmol/L Male
324 7928 4.1 ≥357 μmol/L Female
49 Liu et al. (2016) [60] CS Shanghai East ≥18 8100 9653 83.9 NS Both
2872 3550 81.2 >420 μmol/L Male
5228 6103 85.9 >357 μmol/L Female
50 Liu, Zhou & Yin (2016) [61] CS Yunnan Southwest 32–60 131 390 33.6 NS Both
126 334 37.7 >420 μmol/L Male
5 56 9.1 >360 μmol/L Female
51 Lu (2016) [62] CS Xinjiang Northwest ≥60 233 986 23.6 NS Both
52 Pu et al. (2016) [63] CS Chinaa NAa 20–91 1078 11,967 9.0 NS Both
53 Wang (2016) [64] CS Hubei South Central 18–22 358 4333 8.3 NS Both
294 2029 14.5 >420 μmol/L Male
64 2304 2.8 >350 μmol/L Female
54 Xie et al. (2016) [65] CS Beijing; Tangshan and Zhangjiakou, Hebei North 18–60 632 2782 22.7 NS Both
268 1830 14.6 >420 μmol/L Male
364 952 35.1 >357 μmol/L Female
55 Yang, Wang & Wang (2016) [66] CS Tianjin North 18–93 1165 8968 13.0 NS Both
959 5449 17.6 >417 μmol/L Male
206 3519 5.9 >357 μmol/L Female
56 Zhang (2016) [67] CS Chinaa NAa ≥18 198 794 24.9 >420 μmol/L Male
Eastern Chinaa East ≥18 58 202 31.3 >421 μmol/L Male
57 Zhao et al. (2016a) [68] CS Lanzhou, Gansu Northwest ≥45 37 175 21.1 NS Both
58 Zhao et al. (2016b) [69] CS Beijing North 20 ± 3 1716 6400 26.8 NS Both
1464 4198 34.9 >417 μmol/L Male
252 2202 11.4 >357 μmol/L Female
59 Zhao et al. (2016c) [70] CS Beijing North 20–89 1086 6690 16.2 NS Both
785 3339 23.5 >417 μmol/L Male
301 3351 10.0 >357 μmol/L Female
60 Feng et al. (2017) [71] CS Beijing North range ≥ 18 2257 12,335 18.3 NS Both
1867 7681 24.3 >420 μmol/L Male
390 4654 8.4 >357 μmol/L Female
61 Guo et al. (2017) [72] CS Heilongjiang Northeast 20–59 419 1477 28.4 >420 μmol/L Male
62 He (2017) [73] CS Dalian, Liaoning Northeast 22–91 358 2002 17.9 NS Both
252 1044 24.1 >420 μmol/L Male
106 958 11.1 premenopausal>350 μmol/L postmenopausal>420 μmol/L Female
63 Li et al. (2017) [74] CC Urumqi, Xinjiang Northwest 18–78 221 1644 23.8 NS Both
64 Li, Zhou & Pan (2017) [75] CS Guangdong South Central 22–90 314 3071 10.2 NS Both
65 Lin et al. (2017) [76] CS Yunnan South Central 18–84 196 1682 11.7 NS Both
139 923 15.1 ≥417 μmol/L Male
57 759 7.5 ≥357 μmol/L Female
66 Liu et al. (2017a) [77] CS Shanghai East ≥18 148 908 16.3 NS Both
48 308 15.6 >420 μmol/L Male
100 600 16.7 >360 μmol/L Female
67 Liu et al. (2017b) [78] CS Shanghai East 20–80 1444 9294 15.5 NS Both
639 3393 18.8 >420 μmol/L Male
805 5901 13.6 >357 μmol/L Female
68 Liu et al. (2017c) [79] CS Hunan South Central 20–80 1435 5356 26.8 NS Both
1234 3489 35.4 NS Male
201 1867 10.8 NS Female
69 Liu, Yan & Li (2017) [80] CS Hebei North ≥18 698 6045 11.5 NS Both
488 3344 14.6 >416 μmol/L Male
210 2701 7.8 >357 μmol/L Female
70 Liu & Yang (2017) [81] CC Beijing North 21–67 204 1799 11.3 NS Both
71 Min (2017) CS Shenyang, Liaoning Northeast 74 282 26.2 NS Both
72 Pan & Jiang (2017) [82] CS Fuzhou, Fujian East 75 210 744 28.2 NS Both
196 618 31.7 >420 μmol/L Male
14 126 11.1 >420 μmol/L Female
73 Wang & Bai (2017) [83] CS Ningxia Northwest 22–60 121 1012 12.0 NS Both
99 757 13.1 >420 μmol/L Male
22 255 8.6 >357 μmol/L Female
74 Wang & Bao (2017) [84] CS Shanghai East 60–93 454 2426 18.7 NS Both
220 1076 20.5 >420 μmol/L Male
234 1350 17.3 >360 μmol/L Female
75 Xie et al. (2017) [85] CS Guangdong South Central 35–75 279 2587 10.8 NS Both
175 1410 12.4 >417 μmol/L Male
104 1177 8.8 >357 μmol/L Female
76 Yu & Jie (2017) [86] CS Shandong East 21–76 1191 10,743 11.1 NS Both
1116 6426 10.4 ≥430 μmol/L Male
75 4317 0.7 ≥375 μmol/L Female
77 Zhang (2017a) [87] CS Liaoning Northeast 21–50 121 500 24.2 NS Both
78 Zhang (2017b) [88] CS Anhui East 25–87 19 230 8.3 >420 μmol/L Both
79 Zhang, Chen & Liu (2017) [89] CS Zhuhai, Guangdong South Central 18–75 590 1834 NS Both
290 679 42.7 NS Male
300 1155 26.0 NS Female
80 Zheng (2017) [90] CS Chinaa NAa 24 ± 6 432 1721 25.1 > 420 μmol/L Male
81 Chen et al. (2018a) [91] CS Liaoning, Heilonjiang, Shandong, Henan, Hubei, Hunan, Jiangsu, Guizhou, Guangxi NAb 49 ± 17 1435 8785 16.3 NS Both
886 4110 21.6 ≥420 μmol/L Male
549 4675 11.7 ≥360 μmol/L Female
82 Chen et al. (2018b) [92] CS Guangxi South Central > 60 161 817 19.7 >420 μmol/L Both
83 Chen et al. (2018c) [93] CS Guangdong South Central ≥18 328 981 33.4 >420 μmol/L Male
84 Chen et al. (2018d) [94] CS Guangxi South Central 65–96 241 1223 19.7 NS Both
163 629 25.9 ≥420 μmol/L Male
78 594 13.1 ≥360 μmol/L Female
85 Fan, Mao & Chen (2018) [95] CS Ningbo, Zhejiang East ≥45 750 3395 22.1 NS Both
86 He (2018) [96] CS Henan South Central 25–89 410 2193 18.7 NS Both
305 1156 26.4 >420 μmol/L Male
105 1037 10.1 >350 μmol/L Female
87 Hu et al. (2018) [97] CS Guangxi South Central 20–70 1035 6241 16.6 NS Both
755 3271 23.1 > 420 μmol/L Male
280 2970 9.4 > 360 μmol/L Female
88 Huang & Huang (2018) [98] CS Guangzhou, Guangdong South Central 51–82 55 338 16.3 NS Both
49 289 17.0 NS Male
6 49 12.2 NS Female
89 Huang et al. (2018) [99] CS Guizhou Southwest 18–75 26,341 143,687 18.3 NS Both
15,387 75,364 20.4 ≥417 μmol/L Male
20,954 68,323 16.0 ≥357 μmol/L Female
90 Li, Wang & Xu (2018) [100] CS Beijing North 18–80 255 1700 15.0 NS Both
116 620 18.7 NS Male
139 1080 12.9 NS Female
91 Lin et al. (2018a) [101] CS Fujian East 18–63 666 2666 25.0 NS Both
411 1251 43.9 >417 μmol/L Male
255 1415 18.0 >357 μmol/L Female
92 Lin et al. (2018b) [102] CS Guangzhou, Guangdong South Central ≥18 1642 5603 29.3 NS Both
1590 5281 30.1 >420 μmol/L Male
53 322 16.5 >350 μmol/L Female
93 Lu (2018a) [103] CS Zhejiang East 55 147 1200 12.3 NS Both
93 597 15.6 > 420 μmol/L Male
54 603 9.0 > 350 μmol/L Female
94 Lu (2018b) [104] CH Inner Mongolia North ≥35 383 2554 15.0 NS Both
331 1632 20.3 >420 μmol/L Male
52 922 5.6 >360 μmol/L Female
477 2554 18.7 NS Both
413 1632 25.3 >420 μmol/L Male
64 922 6.9 >360 μmol/L Female
511 2554 20.0 NS Both
446 1632 27.3 >420 μmol/L Male
65 922 7.6 >360 μmol/L Female
530 2554 20.8 NS Both
465 1632 28.5 >420 μmol/L Male
65 922 8.0 >360 μmol/L Female
95 Su et al. (2018) [105] CS Zhejiang East range ≥ 18 694 3905 17.8 NS Both
364 1797 20.3 NS Male
330 2108 15.7 NS Female
96 Tuo et al. (2018) [106] CS Gansu Northwest 20–80 768 4263 18.0 NS Both
432 1783 24.2 ≥420 μmol/L Male
336 2480 13.6 ≥350 μmol/L Female
97 Wang et al. (2018a) [107] CS Beijing; Xi’an, Shaanxi; Harbin, Heilongjiang; Chengdu, Sichuan; Chongqing; Changsha, Hunan; Shanghai NAb ≥60 754 5351 14.1 NS Both
304 2304 13.2 ≥420 μmol/L Male
450 3047 14.8 ≥360 μmol/L Female
98 Wang et al. (2018b) [108] CS Liaoning; Heilongjiang; Jiangsu; Shandong; Henan; Hubei; Hunan; Guangxi NAb ≥18 555 4111 13.5 NS Both
361 1871 19.3 > 418 μmol/L Male
194 2240 8.7 > 357 μmol/L Female
99 Wang & Ma (2018) [109] CS Liaoning Northeast 22–65 432 1481 29.2 > 420 μmol/L Male
100 Yang et al. (2018) [110] CS Chinaa NAa ≥18 3855 24,095 16.0 NS Both
101 Yu et al. (2018) [111] CS Xinjiang Northwest 30–81 2648 14,426 18.4 NS Both
102 Zhang et al. (2018) [112] CS Ningxia Northwest ≥18 3880 19,356 20.0 NS Both
3180 12,115 26.2 >420 μmol/L Male
700 7241 9.7 >350 μmol/L Female
103 Zhou et al. (2018) [113] CS Ningxia Northwest ≥35 279 1743 16.0 NS Both
193 1044 18.5 NS Male
86 699 12.3 NS Female
104 Hu, Zhao & Shang (2019) [114] CS Tibet Northwest 20–49 170 1669 10.2 NS Both
114 952 12.0 NS Male
56 717 7.8 NS Female
105 Tian et al. (2019) [115] CS Beijing North 18–97 10,795 52,673 20.5 NS Both
8524 27,419 31.1 NS Male
2271 25,254 9.0 NS Female
106 Wang et al. (2019) [123] CC Chinaa NAa ≥18 2977 22,983 13.0 NS Both
1999 10,787 18.5 NS Male
978 12,796 7.6 NS Female
107 Yang (2019) [116] CH Guilin, Guangxi South Central 20–68 160 1545 10.4 NS Both
108 Yu et al. (2019) [117] CS Shenyang, Liaoning Northeast ≥18 7705 14,323 53.7 NS Both
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CS Cross-sectional, CC Case control, CH Cohort study, NA Not applicable, NS Not stated

aNo specific provinces were reported

bMore than one region was involved

cMean used unless range reported

Table 2.

Prevalence of hyperuricemia by subgroups in mainland China

Subgroups No. of studies Pooled 95% CI I2 (%) P-value
Region
 East 23 0.173 0.139–0.213 99.844 < 0.001
 North 16 0.174 0.134–0.222 99.241 < 0.001
 Northeast 6 0.246 0.163–0.353 99.873 < 0.001
 Northwest 18 0.155 0.121–0.197 97.447 < 0.001
 South Central 26 0.207 0.170–0.249 99.373 < 0.001
 Southwest 6 0.158 0.102–0.236 99.779 < 0.001
 Overall 95 0.181 0.163–0.201 99.734 0.281
Sex
 Females 83 0.110 0.096–0.126 99.678 < 0.001
 Males 89 0.227 0.202–0.254 99.447 < 0.001
 Overall 172 0.163 0.149–0.178 99.613 < 0.001
Study type
 Cross-sectional 94 0.181 0.164–0.200 99.761 < 0.001
 Cohort 9 0.119 0.082–0.169 95.073 < 0.001
 Case control 4 0.149 0.088–0.240 94.186 < 0.001
 Overall 107 0.174 0.158–0.191 99.735 0.062
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Pooled prevalence of hyperuricemia

The pooled estimate of prevalence in the general population was 0.174 (95%CI: 0.158–0.191) (Fig. 2), which suggested that 17.4% of the population in mainland China had hyperuricemia.

Fig. 2.

Fig. 2

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Forest plot of the pooled prevalence and 95% CI of hyperuricemia among the general population in mainland China

Subgroup analysis

The prevalence of hyperuricemia was analysed in subgroups, which were categorised according to the following categories: provinces/municipalities/autonomous regions, regions (northeast, northwest, north, southwest, south central and east), sex, study type and year.

The pooled prevalence of hyperuricemia by regions ranged from 15.5 to 24.6%. The pooled prevalence in Northeast region was the highest (24.6%), followed by South Central (20.7%), East (17.3%), North (17.4%), Southwest (15.8%), and Northwest (15.5%) (Table 2). In terms of gender distribution, the pooled prevalence of hyperuricemia in males was significantly higher than females (22.7% (95% CI: 20.2–25.4%) vs. 11.0% (95% CI: 9.6–12.6%)) (P < 0.001) (Table 2). For the study types, there was no difference in prevalence (P = 0.062) and the range of prevalence of hyperuricemia was from 11.9 to 18.1%.

Figure 3 shows the prevalence of hyperuricemia in mainland China by different provinces, municipalities and autonomous regions. Shanghai, Jiangxi, Jilin, Liaoning, Fujian, Guangdong and Guangxi reported a high prevalence of hyperuricemia ≥20%, while Hubei, Shandong and Shanxi had a low prevalence of hyperuricemia < 10%. The remaining provinces, municipalities and autonomous regions had a moderate prevalence of hyperuricemia (10–19%). For males, five provinces (i.e. Anhui, Guangdong, Guangxi, Jilin, and Fujian) reported a very high prevalence of hyperuricemia ≥30% and the remaining provinces, municipalities and autonomous regions reported a moderate-to-high prevalence of hyperuricemia ≥10–29%. For females, majority of the provinces, municipalities and autonomous regions reported a low-to-moderate prevalence of hyperuricemia (0–19%), while Guizhou was the only province with high prevalence of hyperuricemia (≥20%).

Fig. 3.

Fig. 3

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Prevalence of hyperuricemia in mainland China according to different provinces, municipalities and autonomous regions

In the general population, there was a downward trend in the prevalence of hyperuricemia from 1995 to 1999 (22.1%) to 2015–2019 (18.6%). Similar downwards trends in the prevalence of hyperuricemia for males and females were also observed.

Analysis of heterogeneity and publication bias

There was a significant heterogeneity in the included studies (I2 = 99.735%, P < 0.001). However, no indications of publication bias were observed as indicated by a symmetrical funnel plot (Fig. 4) and Begg and Mazumdar rank correlation (P = 0.392). The overall results remained unchanged as well after we performed a trim and fill method. Similarly, no publication bias was also reported for the subgroups analysis (Begg and Mazumdar rank correlation with a P-value > 0.05) and all funnel plots were symmetrical.

Fig. 4.

Fig. 4

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Funnel plot for the meta-analysis of the prevalence of hyperuricemia in mainland China

Discussion

We performed a comprehensive meta-analysis of 108 observational studies over two decades and covered 27 provinces, autonomous regions and municipalities in the mainland China. In our meta-analysis, the prevalence of hyperuricemia in the general population of mainland China was 17.4% (22.7% in males and 11.0% in females), which was within the range of reported global prevalence (ranging from 1 to 85%) [8].

Our pooled prevalence was higher than a meta-analysis reported by Liu et al. i.e. 13.3% (19.4% in males and 7.9% in females) [11]. Our prevalence was similar to some developing countries in Asia. In Thailand, the overall prevalence of hyperuricemia was 10.6% in the general population with 18.4 and 7.8% in males and females, respectively [124]. In Turkey, the overall prevalence of hyperuricemia was 12.1% and males had a higher prevalence than females (i.e. 19.0% vs. 5.8%) [125].

However, our results were lower than that reported in developed countries [122, 126]. In the United States, the prevalence of hyperuricemia was 21.2 and 21.6% in males and females, respectively [126]. In Japan, the prevalence of hyperuricemia in the general population was 25.8% (34.5 and 11.6% in males and females, respectively) [122]. The higher prevalence reported in developed countries was most likely due to rapid aging and urbanisation [126]. In addition, the prevalence of non-communicable disease and obesity has also increased in these developed countries [122, 126], which might have contributed to the higher prevalence of hyperuricemia. Therefore, we strongly recommend that the Chinese health authorities should introduce more effective public health policies measures including prevention of obesity programme and promotion of health lifestyles to reduce the prevalence of hyperuricemia in Chinese population.

Since China is a vast country characterised by distinct regions, the prevalence of hyperuricemia varies largely in different provinces and regions. Our results reported that the prevalence of hyperuricemia ranged from 15.8 to 24.6%, with the highest prevalence in the Northeast region. We postulated that the large variability in the prevalence might be caused by the difference in the economic development and sedentary lifestyle adopted in these regions and provinces. For example, those living in Guangxi, Guangdong, Fujian and Jiangxi, people would consume more meat, alcohol and seafood. These foods are rich in purine which can cause an increase in the production of uric acid in the body [127]. Shanghai is one of the most economically developed areas in China. Rapid economic growth has led to unhealthy lifestyles and dietary patterns in the Shanghai population. In addition, an increased inactivity at work has also contributed to a higher prevalence of hyperuricemia [128]. In Jilin and Liaoning, we also reported a high prevalence of hyperruricemia (20–29%), which could be due to the high consumption of alcohol intake, particularly beer and liquor [129]. However, the specific reasons why these regions had a high prevalence require further research. In addition, with these results, the management of hyperuricemia (including routine health check-ups and serum uric acid screening tests) in these regions can be better implemented and improved by the health authorities. Nutrition education and lifestyle interventions can also be developed and specifically targeted to the high risk regions with proper healthcare resources by the health authorities. This is because if hyperuricemia is not well managed and prevented especially in regions with high prevalence, it can induce several medical complication including chronic failure and gout, which increases the cost of medical care [2].

In addition, we reported that males had a significantly higher prevalence of hyperuricemia than females (22.7% vs. 11.0%). Such a difference might be due to the sex hormones [130]. Serum uric acid level is generally higher in males than females. This is because there is an increase renal urate clearance by estrogen in women [129]. Our findings were consistent with the results reported in several countries from Asia and the Asia Pacific region including Nepal [131], Thailand [132], Turkey [125], Saudi Arabia [133], Seychelles [134], Japan [122] and New Zealand [135].

Our study also reported an increasing prevalence of hyperuricemia over time in males and females. We speculated that factors including aging population and obesity have contributed to the increase [126]. However, we also noticed different diagnostic cut-offs were used to diagnose hyperuricemia. It will be helpful to compare these different cut-offs in the same population in order to understand their validity in diagnosing hyperuricemia.

Our meta-analysis has several strengths. Firstly, to our knowledge, our study is the most comprehensive study among the general population in mainland China. Unlike the previous two meta-analyses [10, 11], our sample size (> 808,505 participants) and number of eligible articles (n = 108) were larger; and we included analyses on differences across regions, provinces, sex and study periods. Secondly, our pooled data covered all the six regions in China. In addition, all the provinces, municipalities and autonomous regions were also included, except for Qinghai, Chongqing, Hong Kong, Macao and Hainan. Thirdly, the authors who were involved in the data extraction and interpretation were proficient in the Chinese language. However, our study also suffered from a few limitations. Most of the included articles were cross-sectional studies. Since the definition of hyperuricemia varied according to the diagnostic cut-offs used by different studies, this factor should also be taken into consideration when interpreting these results. There was also a large heterogeneity in the quality of the articles, although no indications of publication bias were reported. We also did not make a clear distinction between urban and rural areas. Therefore, future studies with larger populations should consider investigate if health literacy, health status, sociodemographics and physical activity level play an important factor in the prevention and management of hyperuricemia, especially in adolescents, pregnant women and older adults with lower socioeconomic status [136].

Conclusions

Hyperuricemia has become an important public health problem in mainland China, particularly among males. Special attention should be paid to the residents in geographical regions with high prevalence of hyperuricemia. In addition, our study was the first comprehensive study to investigate the overall prevalence of hyperuricemia in mainland China covering the six regions. Our study also underline the importance of having more larger population-based intervention studies to tackle the increasing problem of hyperuricemia, particularly the vulnerable groups in mainland China. Future studies should investigate the association between the prevalence of hyperuricemia and its risk factors such as geographical region, economic level and sex in order to develop public health policies for tackling the issue.

Acknowledgements

Jiayun Huang would like to thank her parents for providing continuous support in her study.

Abbreviations

CMA

Comprehensive Meta-Analysis

CVD

Cardiovascular disease

SSTIR

Shanghai Science and Technology Innovation Resources Center

CNKI

China National Knowledge Infrastructure

CQVIP

Chinese Scientific Journals Fulltext Database

PRISMA

Preferred Reporting Items for Systematic Reviews and Meta-Analyses

NOS

Newcastle-Ottawa Scale

CI

Confidence intervals

Authors’ contributions

Conceptualization: ZFM & JH. Methodology: JH, ZFM, YZ, ZW, YL, HZ, AC & YYL. Formal analysis: JH, ZFM, YZ, YL, HZ &AC. Roles/Writing - original draft: JH & ZFM; Writing - review & editing: JH, ZFM, YZ, ZW, YL, HZ, AC & YYL. All authors read and approved the final manuscript.

Funding

The authors would like to thank Xi’an Jiaotong-Liverpool University for providing support and funding for this hyperuricemia project (SURF code no. 76). The funder had no role in the design of this study and will not have any role during its execution, analyses, interpretation of the data, or decision to submit results.

Availability of data and materials

Not applicable.

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interest.

Footnotes

Jiayun Huang and Zheng Feei Ma contributed equally to this work.

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