Meta-Analysis Open Access
Copyright ©The Author(s) 2024. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastroenterol. Nov 21, 2024; 30(43): 4636-4656
Published online Nov 21, 2024. doi: 10.3748/wjg.v30.i43.4636
Prevalence of Helicobacter pylori infection in China from 2014-2023: A systematic review and meta-analysis
Lu Xie, Ya-Nan Liu, Peng-Yu Li, Xin-Ning Hu, Xin-Yi He, Rui-Bo Huan, Tai-Long Zhao, Hui-Jun Guo, Department of Acquired Immune Deficiency Syndrome Treatment and Research Center, The First Affiliated Hospital of Henan University of Chinese Medicine, Zhengzhou 450000, Henan Province, China
Lu Xie, Ya-Nan Liu, Xin-Ning Hu, Xin-Yi He, Rui-Bo Huan, Tai-Long Zhao, The First Clinical Medical School, Henan University of Chinese Medicine, Zhengzhou 450046, Henan Province, China
Guang-Wei Liu, Department of Spleen, Stomach, Liver and Gallbladder, The First Affiliated Hospital of Henan University of Chinese Medicine, Zhengzhou 450000, Henan Province, China
Peng-Yu Li, Hui-Jun Guo, Henan Key Laboratory of Viral Diseases Prevention and Treatment of Chinese Medicine, Henan University of Chinese Medicine, Zhengzhou 450000, Henan Province, China
ORCID number: Hui-Jun Guo (0000-0002-2326-4952).
Author contributions: Xie L designed the study and edited the manuscript; Xie L and Liu GW reviewed papers and extracted relevant data; Li PY resolved disagreements; Hu XN and He XY conducted data cross checking; Xie L and Liu YN performed statistical analysis and wrote the manuscript; Li PY, Huan RB and Zhao TL provided comments or suggestions about the manuscript; Guo HJ guided the writing and editing of the article, had primary responsibility for final content; all of the authors read and approved the final version of the manuscript to be published.
Supported by The Zhongyuan Famous Doctor, No. ZYYCYU202012119; Scientific Research Special Project of Traditional Chinese Medicine in Henan Province, No. 2024ZY2004; and Scientific Research Special Project of the National TCM Inheritance and Innovation Center of Henan Provincial Health Commission, No. 2023ZXZX1093.
Conflict-of-interest statement: The authors disclose that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
PRISMA 2009 Checklist statement: The authors have read the PRISMA 2009 Checklist, and the manuscript was prepared and revised according to the PRISMA 2009 Checklist.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Hui-Jun Guo, PhD, Professor, Department of Acquired Immune Deficiency Syndrome Treatment and Research Center, The First Affiliated Hospital of Henan University of Chinese Medicine, No. 19 Renmin Road, Jinshui District, Zhengzhou 450000, Henan Province, China. guohuijun@hactcm.edu.cn
Received: July 3, 2024
Revised: September 19, 2024
Accepted: October 16, 2024
Published online: November 21, 2024
Processing time: 120 Days and 9.6 Hours

Abstract
BACKGROUND

Helicobacter pylori (H. pylori) stands as the predominant infectious agent linked to the onset of gastritis, peptic ulcer diseases, and gastric cancer (GC). Identified as the exclusive bacterial factor associated with the onset of GC, it is classified as a group 1 carcinogen by the World Health Organization. The elimination of H. pylori plays a crucial role in the primary prevention of GC. While the prevalence has declined in recent decades, H. pylori infection is still highly prevalent in China, accounting for a significant part of the disease burden of GC. Therefore, updated prevalence information for H. pylori infection, especially regional and demographic variations in China, is an important basis for the design of targeted strategies that will be effective for the prevention of GC and application of policies for H. pylori control.

AIM

To methodically evaluate the occurrence of H. pylori infection throughout China and establish a reference point for subsequent investigations.

METHODS

A systematic review and meta-analysis was conducted following established guidelines, as detailed in our methodology section.

RESULTS

Our review synthesized data from 152 studies, covering a sample of 763827 individuals, 314423 of whom were infected with H. pylori. We evaluated infection rates in mainland China and the combined prevalence of H. pylori was 42.8% (95%CI: 40.7-44.9). Subgroup analysis indicated the highest prevalence in Northwest China at 51.3% (95%CI: 45.6-56.9), and in Qinghai Province, the prevalence reached 60.2% (95%CI: 46.5-73.9). The urea breath test, which recorded the highest infection rate, showed a prevalence of 43.7% (95%CI: 41.4-46.0). No notable differences in infection rates were observed between genders. Notably, the prevalence among the elderly was significantly higher at 44.5% (95%CI: 41.9-47.1), compared to children, who showed a prevalence of 27.5% (95%CI: 19.58-34.7).

CONCLUSION

Between 2014 and 2023, the prevalence of H. pylori infection in China decreased to 42.8%, down from the previous decade. However, the infection rates vary considerably across different geographical areas, among various populations, and by detection methods employed.

Key Words: Helicobacter pylori; Meta-analysis; Prevalence; Epidemiology; China

Core Tip: Globally, Helicobacter pylori infection continues to be the most prevalent infectious disease, posing substantial public health challenges. Despite a reduction in overall prevalence to 42.8% over the past decade, high rates persist in specific areas and demographics within China, necessitating continued vigilance and targeted interventions.
INTRODUCTION

The presence of Helicobacter pylori (H. pylori) infection is linked to various gastrointestinal conditions and serves as the primary etiological agent for chronic gastritis, peptic ulcers, and gastric cancer (GC). The condition impacts approximately 4.4 billion individuals globally, representing a prevalence rate of around 48.5%, thus posing a significant public health issue on a global scale[1]. In the year 2020, global cancer statistics indicated that there were approximately 1013103 new instances of GC, which corresponded to 768793 fatalities across the globe. Notably, China accounted for 478508 of these new cases and 373706 of the deaths recorded[2]. The occurrence of GC in China is 28.68 per 100000, placing it third among cancers, following lung and colon cancers[3], and it remains a significant contributor to cancer mortality. Despite advancements in sanitation and living conditions, China continues to face a significant prevalence of H. pylori infection and GC. The elimination of H. pylori has been shown to markedly decrease immune and inflammatory responses, promote ulcer healing, and diminish the likelihood of GC development. Long-term studies from Linqu County of Shandong Province and Matsu Island of Taiwan have demonstrated reductions in GC risk by 52% and 53%, respectively, after H. pylori eradication[4,5]. A vast country, China presents a huge variation in geographic, environmental, and socioeconomic aspects of the country; hence, its prevalence rates for diseases also vary significantly amongst its regions. The National Cancer Center, the Cancer Hospital of the Chinese Academy of Medical Sciences, and Peking Union Medical College of China have all documented regional differences in cancer incidence[6]. For example, Qinghai Province exhibits the highest incidence rate of GC in the nation, while Hubei Province is positioned sixth. It is crucial to tailor prevention and treatment strategies to China's unique national circumstances, including the specific epidemiological disease profiles and the diverse needs of various regions and demographics. This is vital for decelerating disease progression and minimizing premature mortality due to end-stage events[7]. Examining the impact of H. pylori infections on disease burden is crucial for formulating national policies[8]. In this research, a meta-analysis approach will be employed, utilizing evidence-based methods with individual rental rates to examine the infection rate within the general population of China. The analysis aids in reliable evidence that is needed at clinical prevention and intervention strategies. The results are as follows.

MATERIALS AND METHODS

This meta-analysis was registered on the PROSPERO database (No. CRD42024555621) and carried out in compliance with the Preferred Items for Systematic Reviews and Meta-Analysis standards.

Search strategy

A systematic review of literature was performed using six databases: (1) PubMed; (2) EMBASE; (3) Cochrane Library; (4) China National Knowledge Infrastructure; (5) Wanfang; and (6) Cqvip, covering the period from January 1, 2014, to January 1, 2024 (Supplementary Table 1).

Inclusion criteria and exclusion criteria

The inclusion criteria were as follows: (1) Patients diagnosed with H. pylori infection via urea breath test (UBT), serological antibody test, stool antigen detection, endoscopic examination, or histopathological evaluation of gastric mucosa biopsies; (2) Studies with clearly defined time and location, involving subjects confirmed to be Chinese; (3) Studies where the infection rate was explicitly stated or could be calculated; and (4) Research findings disseminated in either Chinese or English.

The criteria for exclusion encompassed: (1) Intervention trials, reviews, conference papers, case reports, and meta-analyses; (2) Studies with questionable or incorrect data; (3) Duplicate studies; and (4) Studies with sample sizes less than 50. Literature management was facilitated using Endnote 9.1 software. Two researchers worked separately to search for and screen literature; when they disagreed, they consulted an expert third party to settle the dispute.

Data extraction and quality assessment

Two researchers worked separately to retrieve the data using an Excel spreadsheet. The first author, publication year, study site, geographical area, sample size, and gender distribution of participants were among the data points retrieved. A third researcher resolved any disagreements, and the studies were assessed according to the Loney criterion[9]. Details of these quality assessments are presented in Supplementary Table 2[10-160].

Statistical analysis

The occurrence of H. pylori infection was assessed via meta-analysis. The variation among the studies was evaluated through the application of Cochran’s Q statistic and the I-square statistics (I2). The random-effects model was utilized to calculate the pooled prevalence along with its 95%CI. Sensitivity and subgroup analyses were conducted to further investigate heterogeneity and validate the robustness of the study findings. The subgroup analyses examined the prevalence of H. pylori by province, municipality, autonomous region, geographical area, gender, age, and detection method. Meta-analyses were conducted in RStudio using the "metaprop()" function. Funnel plots were created with the "metabias()" function, and asymmetry was evaluated using the AS-Thompson test[161]. All statistical tests were two-sided, with statistical significance set at P < 0.05.

RESULTS
Literature search and screening results

Figure 1 shows the steps involved in searching for and screening literature. The original list of books included 6430 items; 929 of those were later eliminated due to duplication. We removed 5042 results after going over their titles and abstracts. A detailed review of 459 publications was conducted, resulting in 151 studies being selected for inclusion.

Figure 1
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Figure 1 Literature search and screening process.
Basic characteristics of included literature

This analysis involved 152 studies, with a cumulative sample size of 763827 participants. Zou et al[10] presented two studies meeting the inclusion criteria within a single publication. As a result, the table displaying the basic characteristics of the included literature (Table 1) lists 152 studies, whereas the referenced literature totals 151 articles. The study encompassed thirty provinces, municipalities, and autonomous regions across mainland China, with Zhejiang Province (n = 12), Guangdong Province (n = 10), and Hubei Province (n = 9) recording the highest number of studies. Heilongjiang province was excluded due to the lack of studies that met the inclusion criteria during the search period. East China recorded the most studies (n = 43) among the seven geographic regions, while Northeast China had the fewest (n = 6) (Table 1)[10-160].

Table 1 Characteristics of the included studies.
Ref.
Year
Type of study
Region
Data collection time
Detection methods
Age (range/mean ± SD)
Simple size
Male
Positive (male/female)
Prevalence
95%CI
North East
Zhang et al[11]2016Cross-sectionalJilin (Jilin Province)2014.11-2024.12221-60193244.77293/39535.633.5-37.8
Wang et al[12]2014Cross-sectionalChangchun (Jilin Province)2012.05-2012.12122-83105965.06324/13843.640.6-46.7
Zhang et al[13]2014Cross-sectionalShenyang (Liaoning Province)2012.04-2012.0623-6115052.0079/7213.111.2-15.2
Zhu et al[14]2020Cross-sectionalJinzhou (Liaoning Province)2019.02-2019.04121-61285977.86792/16633.531.8-35.3
Jiang et al[15]2015Cross-sectionalDalian (Liaoning Province)2012.12-2013.1121-100412753.62664/59130.429.0-31.8
Ji and Gu[16]2016Cross-sectionalDalian (Liaoning Province)2013.09-2015.09218-88421447.51480/43721.820.5-23.0
North China
Zheng et al[17]2022Cross-sectionalTangshan (Hebei Province)2019.07-2020.09121-78994467.093115/139545.444.4-46.3
Yang et al[18]2020Cross-sectionalBeijing2013.09-2019.061NA726036.541106/172639.037.9-40.1
Zhao et al[19]2017Cross-sectionalBeijing2009.09-2010.0241 month–18 years119650.6765/6210.68.9-12.5
Xi et al[20]2018Cross-sectionalBeijingNA46-1329155.3347/2023.018.3-28.3
Chen et al[21]2016Cross-sectionalBeijing2012.01-2016.12114-801100051.652826/231346.745.8-47.7
Wu et al[22]2014Cross-sectionalBeijing2010.01-2013.12116-881033169.293236/135344.443.5-45.4
Cui et al[23]2020Cross-sectionalBeijing2018.06-2019.05118-81105852.65175/16331.929.1-34.9
Zhang et al[24]2014Cross-sectional Beijing2010170.9200650.10851/82283.481.7-85.0
Zhang et al[25]2015Cross-sectionalBaoding (Hebei Province)2015220-6137949.3486/8946.241.1-51.3
Chen et al[26]2019Cross-sectionalHohhot (Inner Mongolia Autonomous Region) 2016-2019118-811356856.602480/167730.629.9-31.4
Wang et al[27]2019Cross-sectionalHailar District (Inner Mongolia Autonomous Region)2017.01-2017.1217-881529356.144232/303147.546.7-48.3
Kan et al[28]2015Cross-sectionalChifeng (Inner Mongolia Autonomous Region)2013.1.4-2013.5.31217-91328260.18457/23020.919.6-22.4
Yan et al[29]2020Cross-sectionalChengzhi (Shanxi Province)2019.01-2019.12216-96122469.61536/25965.062.2-67.6
Li et al[30]2022Cross-sectionalShanxi Province2019.01-2021.12120-86336575.99474/19719.918.6-21.3
Zhang et al[31]2021Cross-sectionalTianjin2017.08-2018.08116-901000054.091978/162636.035.1-37.0
East China
Zhang et al[32]2020Cross-sectionalShe County Tongcheng (Anhui Province)NA120-90153639.84389/58163.260.7-65.6
Wang et al[33]2022Cross-sectionalSuzhou (Anhui Province) 2017.01-2020.07121-853363457.737603/564739.438.9-39.9
Peng et al[34]2021Cross-sectionalAnqing (Anhui Province)2019.04-2019.08218-92272560.51816/61052.350.4-54.2
Han et al[35]2021Cohort studyAnhui Province2017.07-2020.111≥ 18109467.92329/15344.141.1-47.1
Guo et al[36]2019Cross-sectionalJieshou (Anhui Province)2017.1-2018.12118-97968445.341356/167631.330.4-32.2
Hu et al[37]2015Cross-sectionalFujian Province2013.02-2013.11218-762770NA143551.849.9-53.7
Xie et al[38]2020Cross-sectionalNingde (Fujian Province)2019.10-2020.01311-8341755.64135/11259.254.3-64.0
Li et al[39]2016Cross-sectionalJinjiang (Fujian Province)2015.01-2015.12117-86875166.672640/144046.645.6-47.7
Liu et al[40]2016Cross-sectionalXiamen (Fujian Province)2012-2014144.8 ± 12.3144466.90475/21647.945.2-50.5
Chen et al[41]2022Cross-sectionalZhangzhou (Fujian Province)2019.09-2020.08120-89260854.79655/59447.946.0-49.8
Mao et al[42]2017Cross-sectionalSuzhou (Jiangsu Province)2015.01-2015.12120-8096377.15333/9244.141.0-47.3
Zhang et al[43]2019Cross-sectionalNanjing (Jiangsu Province)2017.05-2017.08164.34 ± 8.3293534.33126/23935.932.9-39.1
Xie et al[44]2017Cross-sectionalSuzhou (Jiangsu Province)2015.10-2016.07112-93266452.74769/75357.155.2-59.0
Jiang et al[45]2015Cross-sectionalJiangsu Province2013.01-2014.10117-95348062.44949/61544.943.3-46.6
Li et al[46]2019Cross-sectionalNanjing (Jiangsu Province)2019148.75 ± 5.9770057.14132/12436.633.0-40.3
Wang et al[47]2023Cross-sectionalNanjing (Jiangsu Province)20221NA1516054.472721/190630.529.8-31.3
Meng et al[48]2015Cross-sectionalDongtai (Jiangsu Province)2012.06-2013.6129-75159852.00403/30744.442.0-46.9
Ji et al[49]2023Cross-sectionalSuzhou (Jiangsu Province)2018.1-2018.12218-89658864.312370/133956.355.1-57.5
Zhang et al[50]2018Cross-sectionalJiuzhou (Jiangxi Province)2015.07-2016.10118-90120054.9258048.345.5-51.2
Ren et al[51]2020Cross-sectionalPingxiang (Jiangxi Province)2016.01-2019.0629-921048758.813011/201047.946.9-48.8
Wang et al[52]2017Cross-sectionalJiuzhou (Jiangxi Province)2016.01-2017.03143.89616574.161689/63637.736.5-38.9
Fang et al[53]2021Cross-sectionalJingdezhen (Jiangxi Province)2008.7-2019.1216-954835350.0810462/1030142.942.5-43.4
Xu et al[54]2019Cross-sectionalCao County (Shandong Province)2018.04-2018.07118-90118249.49198/17531.628.9-34.3
Shi et al[55]2022Cross-sectionalXintai (Shandong Province)2021.04-2022.04118-8440052.50106/4638.033.2-43.0
Li et al[56]2015Cross-sectionalJining (Shandong Province)2012.05-2013.051, 216-7258056.03156/10645.241.1-49.3
Liang et al[57]2014Cross-sectionalJining (Shandong Province)2012.02-2012.12116-74436668.601690/75055.954.4-57.4
Han et al[58]2020Cross-sectionalJining (Shandong Province)2017.01-2017.12219-91255769.42782/46657.455.4-59.3
Kong et al[59]2022Cohort studyShandong Province2021.07-2022.011NA117347.06204/22636.733.9-39.5
Zhang et al[60]2019Cross-sectionalShanghai2017.01-2018.01118-90516452.051008/86936.335.0-37.7
Sun et al[61]2018Cross-sectionalShanghai2016.09-2016.12240-93325843.92451/46128.026.5-29.6
Jia et al[62]2020Cross-sectionalShanghai2018.10-2019.9125-702998659.7911547/603358.658.1-59.2
Qiu et al[63]2022Cross-sectionalHanghzou (Zhejiang Province)2019.09-2019.11121-6922554.6731/3931.125.1-37.6
Yu et al[64]2018Cross-sectionalJiaxing (Zhejiang Province)2016.01-2017.061, 318-80422047.44900/70938.136.7-39.6
Zhou et al[65]2023Cross-sectionalWenzhou (Zhejiang Province)2020.01.1-2022.08.1218-7156885.56197/3841.437.3-45.5
Zheng et al[66]2015Cross-sectionalHanghzou (Zhejiang Province)2013.06-2014.05112-76222063.96658/30943.641.5-45.7
Yang et al[67]2015Cross-sectionalWenzhou (Zhejiang Province)2013.10-2014.41≥ 201581760.795078/352556.956.1-57.7
Lin et al[68]2014Cross-sectionalCangnan County (Zhejiang Province)2007.06-2012.12318-701198658.06335128.027.2-28.8
Yang et al[69]2015Cross-sectionalTaizhou (Zhejiang Province)2011.01-2013.12120-70207253.28376/33634.432.3-36.5
Wang et al[70]2015Cross-sectionalWenzhou (Zhejiang Province)2010.04-2015.0220-144520NA211846.945.4-48.3
Li et al[71]2017Cross-sectionalAnji County (Zhejiang Province)2015.01-2016.01418-8094351.22242/25953.149.9-56.4
Shen et al[72]2014Cross-sectionalHanghzou (Zhejiang Province)2012.1-2012.12220-91791154.252180/185050.949.8-52.0
He et al[73]2016Cross-sectionalJiangshan (Zhejiang Province)2014.05-2015.0823-5314350.56390/35823.822.3-25.3
Fang et al[74]2022Cross-sectionalJinhua (Zhejiang Province)2019.1-2021.122NA206050.58542/52351.749.5-53.9
Northwest China
Yu et al[75]2016Cross-sectionalLanzhou (Gansu Province)2014.05-2015.07116-96323970.361197/48251.850.1-53.6
Xie[76]2021Cross-sectionalYuan County (Gansu Province)2016.01-2020.01112-84236943.31694/92768.466.5-70.3
Zou et al[77]2018Cross-sectionalGansu Province2015.1-2015.12227-87133844.8499/7713.211.4-15.1
Qin et al[78]2018Cross-sectionalJingtai County (Gansu Province)2013.05-2017.061≥ 14718249.711667/189049.648.5-50.8
Wu et al[79]2016Cross-sectionalLanzhou (Gansu Province)2013.07-2015.06218-8144257.24137/8951.146.4-55.9
Li[80]2016Cross-sectionalZhangye County (Gansu Province)2014.01-2015.12118-83100052.10297/26356.052.9-59.1
Ma et al[81]2018Cross-sectionalBaiyin (Gansu Province)2018120-701672252.764290/280242.441.7-43.2
Hou et al[82]2020Cross-sectionalQingyang (Gansu Province)2016.1-2019.1228-92832160.062894/220661.360.2-62.3
Zhang et al[83]2020Cross-sectionalYinchuan (Ningxia Hui Autonomous Region)2018.06-2018.091≥ 1880050.00243/21156.853.2-60.2
Hu et al[84]2019Cross-sectionalNingxia Hui Autonomous Region2018.12-2019.12114-8871033.10146/25756.853.0-60.4
Li et al[85]2024Cross-sectionalQinghai Province2021-202213-85113142.44241/35652.849.8-55.7
Li et al[86]2022Cross-sectionalQinghai Province2021.05-2012.1214-90472442.651047/148453.652.1-55.0
Wang et al[87]2019Cross-sectionalQinghai Province2017.08-2018.11114-85210348.64775/78474.172.2-76.0
Zhang et al[88]2014Cross-sectionalXian (Shaanxi Province)2014.01-2014.02121-8254874.09191/7248.043.7-52.3
Zhang et al[89]2015Cross-sectionalXian (Shaanxi Province)2009-2013218-701650659.952983/167127.727.0-28.3
Tang et al[90]2017Cross-sectionalXian (Shaanxi Province)2016118-78608546.051463/158550.148.8-51.4
Xiao et al[91]2021Cross-sectionalXian (Shaanxi Province)2019.5-2020.051NA210060.81600/38346.844.7-49.0
Di et al[92]2022Cross-sectionalXian (Shaanxi Province)2016.09-2020.1215-961001645.061753/150232.531.6-33.4
Zhu et al[93]2017Cross-sectionalHoboksar (Xinjiang Uygur Autonomous Region)NA1, 220-78120043.58362/48070.267.5-72.7
Yao and Wang[94]2017Cross-sectionalUrumqi (Xinjiang Uygur Autonomous Region)2016.05.10-2016.11.241NA230143.29455/58545.243.1-47.3
Li et al[95]2023Cross-sectionalTarbagatay Prefecture (Xinjiang Uygur Autonomous Region)2019.01-2022.062NA284050.56846/77156.955.1-58.8
Wang et al[96]2016Cross-sectionalXinjiang Uygur Autonomous Region2013.06-2014.06117-87478056.191264/104548.346.9-49.7
Fan et al[97]2016Cross-sectionalXinjiang Uygur Autonomous Region2014.09-2015.09116-75477441.101243/189065.664.3-67.0
Southwest region
Shu[98]2021Cross-sectionalTongren County (Guizhou Province)2018.04-2019.04120-6080056.38252/20156.653.1-60.1
Yang et al[99]2019Cross-sectionalAba Tibetan and Qiang Autonomous Prefecture (Sichuan Province)2015.05-2016.1212-9254446.5173/9330.526.7-34.6
Zhou et al[100]2022Cross-sectionalGuangyuan (Sichuan Province)2020.3-2021.03118-81429644.411140/112852.851.3-54.3
Xu et al[101]2019Cross-sectionalLuzhou (Sichuan Province)2017.05-2018.051, 214-871868463.353788/208631.430.8-32.1
Xiao et al[102]2020Cross-sectionalYibin (Sichuan Province)2017.01-2018.1242-662254.9871/6021.117.9-24.5
Luo et al[103]2022Cross-sectionalNanchong (Sichuan Province)2021.8-2022.51≥ 18147850.47375/32747.544.9-50.1
Zou et al[10]2023Cross-sectionalChengdu (Sichuan Province)2013-20141NA1691452.493640/334141.340.5-42.0
Zou et al[10]2023Cross-sectionalChengdu (Sichuan Province)2019-20211NA1828146.742570/303530.730.0-31.3
Wu et al[104]2017Cross-sectionalThe Tibet Autonomous RegionNA1, 32-85433253.461475/120861.960.5-63.4
Cai et al[105]2018Cross-sectionalLhasa (The Tibet Autonomous Region)2015.11-2016.715-85100044.30245/33157.654.5-60.7
Dawa et al[106]2021Cross-sectionalThe Tibet Autonomous Region2018-20191NA71752.44196/19254.150.4-57.8
Zhang et al[107]2021Cross-sectionalBaishe (Yunnan Province)2020.04-2020.0843-632150.47159/4025.921.2-31.0
Xie[108]2017Cross-sectionalQujing (Yunnang Province)2016.1-2016.12120-79879058.071712/117232.831.8-33.8
Wang et al[109]2015Cross-sectionalYunang Province2013.01-2014.081≥ 20668072.541988/68840.138.9-41.2
Li et al[110]2018Cross-sectionalKunming (Yunnan Province)2015.01-2017.12120-7560636.63115/7531.427.7-35.2
Jia et al[111]2018Cross-sectionalYunnan Province2013.01-2015.02121-85168077.74433/19137.134.8-39.5
Fu et al[112]2018Cross-sectionalKunming (Yunnan Province)2013.1-2016.1213-181293253.151706/140824.123.3-24.8
Ding et al[113]2017Cross-sectionalDali (Yunnan Province)2014.06-2016.0640-14112751.4675/5311.49.6-13.4
Chen and Sun[114]2019Cross-sectionalPuer (Yunnan Province)2018.5.1-2019.4.30118-921532856.363793/250241.140.3-41.9
Liu et al[115]2017Cross-sectionalChongqing2014.1-2014.12144.1 ± 10.81091252.911949/180134.433.5-35.3
Liu and Lei[116]2020Cross-sectionalChongqing2017.01-2018.0617-18198250.15109/12111.610.2-13.1
Zhou[117]2018Cross-sectionalChongqing2012.01-2016.081, 338.7100054.60324/20352.749.6-55.8
Meng and Sun[118]2018Cross-sectionalChongqing2017.1-2017.12215-852766259.164222/257624.624.1-25.1
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NA: Not available.
The pooled prevalence of H. pylori in Mainland China

The prevalence of H. pylori infection was analyzed in 152 studies. The heterogeneity test produced an I2 = 99.7%, P < 0.001, necessitating the use of a random-effects model. The combined findings suggest that the prevalence of H. pylori infection in China from 2014 to 2023 stood at 42.8% (95%CI: 40.7-44.9). The corresponding forest plot is shown in Supplementary Figure 1[10-160].

Subgroup analysis

Owing to substantial heterogeneity among the studies, prevalence rates were separately analyzed based on province, municipality, autonomous region, geographic region, gender, age, detection method, and publication year (Figure 2).

Figure 2
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Figure 2 Subgroup analysis of Helicobacter pylori prevalence. N: Number of included studies; UBT: Urea breath test; RUT: Rapid urease test.

Among the 30 provinces, municipalities, and autonomous regions, the highest prevalence of H. pylori was observed in Qinghai Province at 60.2% (95%CI: 46.5-73.9), and the lowest in Liaoning Province at 24.7% (95%CI: 15.7-33.7). Forest plots detailing the prevalence across these areas are presented in Supplementary Figure 2. A bubble diagram illustrating the incidence of H. pylori across these administrative divisions and geographic areas is provided in Figure 3. Of the seven geographical regions, the Northwest exhibited the highest prevalence at 51.3% (95%CI: 45.6-56.9), while the Northeast had the lowest at 29.6% (95%CI: 21.0-38.2). These forest plots are available in Supplementary Figure 3.

Figure 3
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Figure 3 Bubble diagram of Helicobacter pylori prevalence.

Regarding gender differences, the prevalence of H. pylori was slightly higher in males at 44.1% (95%CI: 41.9-46.4) than in females at 41.6% (95%CI: 39.3-44.0); these findings are depicted in Supplementary Figure 4. The meta-analysis revealed that the prevalence of H. pylori was 27.0% (95%CI: 19.9-34.0) in minors and 42.6% (95%CI: 39.9-45.2) in adults. Among the elderly (≥ 60 years), a higher prevalence of 44.5% (95%CI: 41.9-47.1) was noted (Supplementary Figures 5 and 6).

Concerning detection methods, 97 studies used the UBT and 2 studies employed the Rapid Urease Test (RUT). The infection rates were 43.7% (95%CI: 41.4-46.0) using the UBT, 42.5% (95%CI: 37.9-47.2) with the serum antibody test, 43.5% (95%CI: 12.9-74.2) using the RUT, and 24.1% (95%CI: 11.7-36.6) with the H. pylori stool antigen method. The highest infection rate was detected by the UBT method, while the lowest was by the H. pylori stool antigen method. Forest plots for these testing modalities are included in Supplementary Figure 7. From the literature spanning 2014-2018, the prevalence of H. pylori infection was 42.2% (95%CI: 39.2-45.3), and from 2019-2024, it was 43.3% (95%CI: 40.4-46.2). The slight increase in prevalence over these periods was not statistically significant (Supplementary Figures 8 and 9).

Sensitivity analysis

Sensitivity analysis of the combined results was performed using the "leave-one-out" method. The robustness of the study results was confirmed as there were no significant changes; this analysis is shown in Supplementary Figure 10.

Publication bias assessment

Publication bias was evaluated using a funnel plot and the AS-Thompson test, with arcsine transformation used in cases of significant heterogeneity. The analysis yielded a symmetrical funnel plot (t = 1.42, P = 0.157), indicating minimal publication bias. These results are visually displayed in Supplementary Figure 11 and 12.

DISCUSSION

H. pylori, a gram-negative microaerobic bacterium, forms colonies on the epithelial surfaces of the human gastric mucosa, leading to chronic infections[162]. This bacterium has a global prevalence, affecting approximately fifty percent of the world's population, thereby constituting a significant health issue. While a significant majority of infected individuals exhibit no symptoms, the infection carries considerable health implications, as 1%-3% of those affected may progress to GC, and 0.1% may develop mucosa-associated lymphoid tissue lymphoma[163]. The optimal initial therapeutic approach involves a combination of proton pump inhibitors (PPI), amoxicillin, and clarithromycin, commonly referred to as PPI, amoxicillin, and clarithromycin. In regions with elevated primary clarithromycin resistance, bismuth-based quadruple therapies are becoming a favored alternative[164]. Additionally, traditional Chinese medicine[165,166] and microecological agents[167,168] have become crucial in boosting eradication rates and combating drug resistance to H. pylori.

Given the demographic and regional disparities in China, understanding the prevalence of H. pylori is vital for informing future research and healthcare strategies.

This study revealed that the infection rate of H. pylori in China from 2014 to 2023 was 42.8% (95%CI: 40.7-44.9), a decrease from the rates reported in earlier periods by Ren et al[3] from 1990 to 2019 (44.2%, 95%CI: 43.0-45.5) and Li et al[169] from 1983 to 2020 (49.6%, 95%CI: 46.9-52.4). Research by Li et al[170] suggests that the global estimated prevalence of H. pylori decreased from 58.2% (95%CI: 50.7-65.8) between 1980 and 1990 to 43.1% (95%CI: 40.3-45.9) between 2011 and 2022. With the continuous improvement of living environment and hygiene level, and the increasing coverage of basic medical security, the prevalence of H. pylori in China has also shown a downward trend, similar to the global trend of H. pylori prevalence.

The ingestion of raw water and the consumption of vegetables and fruits that have been washed from contaminated water sources represent risk factors for H. pylori infection[171,172]. Nevertheless, the dissemination of H. pylori infections has been constrained alongside enhancements in living standards and hygiene, including augmented access to clean water and more effective sewage treatment[173]. Public awareness of H. pylori and its modes of transmission also resulted in reducing infection rates[174,175]. Studies[176,177] have shown that the public's knowledge about H. pylori and how it is spread has increased in the last decade. The detection of H. pylori infection has been included in the health examination items. The rapid, simple and reliable detection method has been preliminarily accessible. The awareness of active medical treatment among infected people was significantly enhanced[7]. The above reasons have all contributed to the decline of H. pylori infection rate in China in the past decade.

However, the diseases associated with them remain among the great challenges to public health. This report presents updated comprehensive trends in clinically significant and relevant H. pylori infection based on a critical analysis of 152 studies that have been published over the past decade. The results of this study is of a certain credibility and timeliness, and has a certain clinical reference value.

The highest prevalence rate of H. pylori infection was found in Northwest China, which showed a percentage of 51.3% (95%CI: 45.6-56.9). In the northwest region, it is highly prevalent in Qinghai Province, showing a prevalence of 60.2% (95%CI: 46.5-73.9). On the contrary, the lowest infection rates were observed in Northeast China, where the prevalence was 29.6% (95%CI: 21.0-38.2), and the minimum rate was in Liaoning Province at 24.7% (95%CI: 15.7-33.7).

H. pylori has co-evolved with the human host ever since its origin. Local transmission and genetic isolation have facilitated the development of different bacterial populations that are characteristic for geographical areas[178]. You et al[179] conducted a comparative genomic analysis of the genomic sequence features of Chinese H. pylori, and the results of Neighbor Joining analyses of 10 Chinese H. pylori strains showed geographic clustering of H. pylori strains in China. Geographical factors play a long-term and fundamental role in regional development. The expansive northwest region of China, distinguished by its extensive deserts and delicate ecosystems, also sustains robust animal husbandry and a considerable population of nomadic herders. Inhabitants predominantly consume a meat-rich diet[180], with vegetable intake falling below the levels suggested by the Chinese Balanced Dietary Pagoda[181]. The economic development in Northwest China is relatively underdeveloped, and compared with other regions, the allocation of health resources is insufficient[182]. Oral-oral and fecal-oral pathways stand as the primary mechanisms for the transmission of H. pylori, which tends to cluster within families[183]. The region of Northeast China is characterised by fertile land, abundant water and food resources, rich mineral resources and a relatively early economic start. The long winter season and low population density serve to restrict the dissemination of H. pylori infection. Although infection rates in the Northeast are comparably low, the prevalent antibiotic resistance remains a substantial issue[184]. Two provinces in the Southwest region, Qinghai-Tibet (58.1%; 95%CI: 53.6-62.6) and Guizhou Province (56.6%; 95%CI: 53.1-60.1), have particularly high infection rates.

Zhang et al[185] has shown that the high rates of H. pylori infection and GC among Tibetan residents of the plateau are not only related to the backward level of health and economy, but also to the environmental characteristics of the plateau. The frigid, oxygen-deprived conditions of the plateau can result in gastric mucosal injury and disruption to the intestinal barrier, thereby enhancing susceptibility[186]. The Guizhou Province region has a humid climate and the locals enjoy spicy diets and pickled foods. Both were found to be independent risk factors for H. pylori infection[187,188].

Consequently, elements such as environmental conditions, economic status, and sanitation practices collectively impact the prevalence of H. pylori to varying extents.

Addressing the pronounced prevalence of H. pylori infection in Northwest China, particularly given the high incidence and mortality rates of GC in Qinghai Province and Guizhou Province[6], we should launched health education initiatives in these high-incidence and high-risk areas to improve the population's awareness of the risks associated with H. pylori, alongside the available treatment options and their benefits.

So as to fostering changes in knowledge, attitudes, and behaviors, and enable general population actively participate in the work of prevention, screening and treatment of H. pylori. This approach additionally facilitates the primary prevention of GC[177,189]. In regions characterized by heightened antibiotic resistance, the use of antibiotics should be meticulously regulated. Where conditions permit, treatment programmes can be tailored to the antibiotic susceptibility results of individual patients. Compared to these high prevalence areas, infections in other areas are not as serious. However, the prevention and treatment of the disease should not be neglected. In these areas, the compliance of infected people with prescribed treatment and re examination should be improved in order to improve the eradication rate[190]. At the same time, family based management and treatment strategies should be implemented to avoid reinfection. Promote a healthy diet and reduce the intake of ultra-processed food; develop good living habits and actively prevent the occurrence of H. pylori infection[191].

In this study, the prevalence of infection was notably higher in adults compared to minors, with significant prominence in the elderly (> 60 years) (Supplementary Figure 5 and 6). The elderly are more susceptible due to distinctive gastric features, including delayed gastric emptying[192], diminished glandular function[193,194], and a less diverse microbial environment in the stomach[195,196]. People worldwide are living longer. The worldwide demographic is experiencing a significant increase in age, with forecasts from the World Health Organization suggesting that the population aged 60 years and above will double to 2.1 billion by the year 2050[197]. H. pylori is associated with gastrointestinal disturbances as well as the development of various systemic diseases. Studies suggest that H. pylori infection could increase the likelihood of developing neurodegenerative disorders, including Alzheimer's disease[198,199] and Parkinson's syndrome[200], in addition to cardiovascular diseases[201]. In treating the elderly, medical professionals must consider factors like antibiotic resistance, potential drug interactions, and adherence to medication, while carefully balancing the risks and benefits of eradication therapy[202,203].

The incidence of H. pylori infection in pediatric populations shows considerable variation internationally, with reported rates ranging from 3.2% to 84%, influenced by factors including geographical location, environmental conditions, diagnostic techniques, host specificity, and the timing of the study[204]. Factors such as early exposure to pre-chewed food, familial history of gastric disorders, the sharing of personal hygiene items like towels and mouthwash cups[205,206], and low socioeconomic status[207] are significant contributors to the risk of H. pylori infection in children. Recent updated guidelines do not recommend the "test-and-treat" approach for asymptomatic H. pylori infections in pediatric populations, referencing a lack of substantial evidence supporting its effectiveness in reducing the risk of future GC[208].

Regarding detection methods, the highest infection rate identified by the UBT was 43.7% (95%CI: 41.4-46.0), surpassing those detected by serological tests, stool antigen tests, and RUT. Ma et al[139] reported an H. pylori positivity rate of 26.85% utilizing an immunocolloidal gold assay for interdental tartar in subjects. The UBT, preferred for its non-invasive, painless, and repeatable nature, includes two variations: 13C-UBT and 14C-UBT, with the former being more sensitive, non-radioactive, and therefore safer[209]. Recent global guidelines endorse the UBT as the preferred diagnostic tool for H. pylori, recommending it for both initial diagnosis and post-eradication evaluation[210-212], with an emphasis on maintaining stringent quality controls to improve the test's precision. The monoclonal-based stool antigen test also remains a reliable, recommended method with comparable accuracy to the UBT, particularly beneficial for children under six who are less suited for UBT[213]. Serum H. pylori antibody tests are predominantly used in clinical epidemiological studies to ascertain both past and current infections[164,214], and their diagnostic accuracy is enhanced when used in conjunction with UBT[215]. However, the value of serological screening is limited in areas with low infection rates[216]. The identification of H. pylori subtypes aids in assessing infection status and virulence, and can forecast the development of GC[217]. Although RUTs are highly sensitive, their specificity is compromised by factors like sample size and the focal distribution of H. pylori in the stomach[218]. Selecting a diagnostic approach requires consideration of regional infection rates, clinical scenarios, patient age, among other factors, to ensure the selection of suitable and reliable tests for effective treatment planning.

This study's strengths are evident in: (1) Utilizing recent literature spanning the last ten years to mirror the current situation of H. pylori infection; (2) Conducting an exhaustive examination of H. pylori's current prevalence in China, pinpointing key demographics and areas where infection rates are heightened; (3) Incorporating a significant corpus of studies with ample sample sizes, excluding any with fewer than 50 subjects to reduce potential small-sample biases; and (4) Rigorous adherence to established protocols for selecting literature and extracting data, supplemented by cross-validation to enhance the reliability of findings.

The limitations of this study include the following: (1) Some provinces and diagnostic modalities in this study had a low number of included studies, which may have had some impact on the results; and (2) Although we performed subgroup analyses for the results of the study in terms of geographic region, testing modality, age, gender, and so on, there was still a large degree of heterogeneity in the study.

CONCLUSION

In summary, the prevalence of H. pylori infection in China from 2014-2023 is 42.8% (95%CI: 40.7-44.9), marking a decrease from the preceding decade. The rates of H. pylori infection vary depending on geographic location, detection methods, and population demographics. Given the substantial disease burden associated with H. pylori infections, further studies into the mechanisms behind the disparities in H. pylori prevalence, both in China and globally, is both significant and urgent.

ACKNOWLEDGEMENTS

We are very grateful to every participant for their support and contributions to this study.

Footnotes

Provenance and peer review: Unsolicited article; Externally peer reviewed.

Peer-review model: Single blind

Specialty type: Gastroenterology and hepatology

Country of origin: China

Peer-review report’s classification

Scientific Quality: Grade B, Grade C, Grade C

Novelty: Grade B, Grade B, Grade B

Creativity or Innovation: Grade B, Grade B, Grade B

Scientific Significance: Grade B, Grade B, Grade B

P-Reviewer: Zhang W; Zhang J S-Editor: Luo ML L-Editor: A P-Editor: Zheng XM

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