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  <front>
    <journal-meta>
      <journal-id journal-id-type="publisher-id">jbm</journal-id>
      <journal-title-group>
        <journal-title>Journal of Biosciences and Medicines</journal-title>
      </journal-title-group>
      <issn pub-type="epub">2327-509X</issn>
      <issn pub-type="ppub">2327-5081</issn>
      <publisher>
        <publisher-name>Scientific Research Publishing</publisher-name>
      </publisher>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="doi">10.4236/jbm.2024.1212009</article-id>
      <article-id pub-id-type="publisher-id">jbm-137934</article-id>
      <article-categories>
        <subj-group>
          <subject>Article</subject>
        </subj-group>
        <subj-group>
          <subject>Biomedical</subject>
          <subject>Life Sciences</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>Comparative Analysis of Helicobacter pylori Infection Status in High Altitude and Plain Areas of China</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <name name-style="western">
            <surname>Ying</surname>
            <given-names>Linjun</given-names>
          </name>
          <xref ref-type="aff" rid="aff1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <name name-style="western">
            <surname>Huang</surname>
            <given-names>Cheng</given-names>
          </name>
          <xref ref-type="aff" rid="aff1">1</xref>
        </contrib>
        <contrib contrib-type="author" corresp="yes">
          <name name-style="western">
            <surname>Liu</surname>
            <given-names>Xiaoqin</given-names>
          </name>
          <xref ref-type="aff" rid="aff1">1</xref>
        </contrib>
      </contrib-group>
      <aff id="aff1"><label>1</label> Health Management Center, Deyang People’s Hospital, Deyang, China </aff>
      <author-notes>
        <fn fn-type="conflict" id="fn-conflict">
          <p>The authors declare no conflicts of interest regarding the publication of this paper.</p>
        </fn>
      </author-notes>
      <pub-date pub-type="epub">
        <day>02</day>
        <month>12</month>
        <year>2024</year>
      </pub-date>
      <pub-date pub-type="collection">
        <month>12</month>
        <year>2024</year>
      </pub-date>
      <volume>12</volume>
      <issue>12</issue>
      <fpage>109</fpage>
      <lpage>123</lpage>
      <history>
        <date date-type="received">
          <day>29</day>
          <month>10</month>
          <year>2024</year>
        </date>
        <date date-type="accepted">
          <day>01</day>
          <month>12</month>
          <year>2024</year>
        </date>
        <date date-type="published">
          <day>04</day>
          <month>12</month>
          <year>2024</year>
        </date>
      </history>
      <permissions>
        <copyright-statement>© 2024 by the authors and Scientific Research Publishing Inc.</copyright-statement>
        <copyright-year>2024</copyright-year>
        <license license-type="open-access">
          <license-p> This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( <ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by/4.0/">https://creativecommons.org/licenses/by/4.0/</ext-link> ). </license-p>
        </license>
      </permissions>
      <self-uri content-type="doi" xlink:href="https://doi.org/10.4236/jbm.2024.1212009">https://doi.org/10.4236/jbm.2024.1212009</self-uri>
      <abstract>
        <p><bold>Background:</bold> China has a high prevalence of <italic>HP</italic> infection, and the rate of <italic>HP</italic> infection in highland populations is higher than the average rate of <italic>HP</italic> infection in natural populations. However, there is a lack of comparative studies on the current status of <italic>HP</italic> infection in high- and low-altitude. Therefore, this study aims to investigate the current status and differences in <italic>HP</italic> infection between the health check-up populations in the highland region and the plain area. <bold>Methods:</bold> This is a multicenter cross-sectional study, using convenience sampling method, which included the health check-up population of Ruoergai County People’s Hospital and the health check-up population of Deyang City People’s Hospital from January 2023 to December 2023, to carry out the questionnaire survey of <italic>HP</italic>-related factors, and to detect <italic>HP</italic> infection by a <sup>13</sup>C-urea breath test. <bold>Results:</bold> The number of positives was 144 out of 260 health checkups in the plateau region, with a detection rate of 55.4%, which was significantly higher than that of 29.8% in the plains (P &lt; 0.05). In the <italic>H. pylori</italic> infection-positive population, the health checkups in the plateau group had a lower education level, a higher proportion of overweight and obesity, a higher proportion of frequent smokers, a higher frequency of frequent eating out, and a lower proportion of abnormalities of uric acid, total cholesterol, LDL cholesterol, alanine aminotransferase, aspartate aminotransferase, and direct bilirubin but a higher proportion of abnormalities of total bilirubin. There was no statistically significant difference between the two groups in terms of age, gender, history of alcohol consumption, family history, urea, creatinine, and blood glucose. <bold>Conclusion:</bold> Preliminary results indicate that the rate of <italic>HP</italic> infection in the plateau population is significantly higher than that in the plains, and <italic>HP</italic>-related health education should be strengthened in the plateau region.</p>
      </abstract>
      <kwd-group kwd-group-type="author-generated" xml:lang="en">
        <kwd>&lt;i&gt;Helicobacter &lt;/i&gt;&lt;i&gt;pylori&lt;/i&gt;</kwd>
        <kwd>Epidemiology</kwd>
        <kwd>Cross-Sectional Study</kwd>
        <kwd>Health Check-Up Population</kwd>
        <kwd>Plateau</kwd>
        <kwd>Plain</kwd>
      </kwd-group>
    </article-meta>
  </front>
  <body>
    <sec id="sec1">
      <title>1. Background</title>
      <p><italic>Helicobacter pylori</italic> (<italic>HP</italic>) infection is a major cause of chronic gastritis, peptic ulcer, gastric mucosa-associated lymphoid tissue lymphoma, and gastric cancer, as well as being closely associated with a variety of extra gastrointestinal diseases [<xref ref-type="bibr" rid="B1">1</xref>][<xref ref-type="bibr" rid="B2">2</xref>]. It has been reported that approximately half of the global population is infected with <italic>HP</italic> [<xref ref-type="bibr" rid="B3">3</xref>]. Although the <italic>HP</italic> infection rate in China has continued to decline over the past decades (overall infection rate of 58.3% during 1983-1994 and 40.0% during 2015-2019) [<xref ref-type="bibr" rid="B4">4</xref>][<xref ref-type="bibr" rid="B5">5</xref>], the disease burden associated with <italic>HP</italic> is still significant due to the large population base. Therefore, the investigation and prevention of <italic>HP</italic> infection has become a public health issue of particular concern to the medical field in China.</p>
      <p><italic>HP</italic> infection has a global distribution, and the prevalence of <italic>HP</italic> infection in different populations varies greatly depending on age, family history of gastric cancer, geographic location, regional economic development, and sanitary conditions [<xref ref-type="bibr" rid="B3">3</xref>][<xref ref-type="bibr" rid="B6">6</xref>]. An epidemiologic survey in 2021 that included a total of 10,735 households (31,098 individuals) in 29 provinces in mainland China, excluding Guangxi and Xizang, showed that the prevalence of individual <italic>HP</italic> infection in the 29 provinces ranged from 25.33% to 59.61% [<xref ref-type="bibr" rid="B7">7</xref>]. A recent meta-analysis of the temporal and spatial distribution of <italic>HP</italic> infections in mainland China also showed that the plateau is a high-prevalence area for <italic>HP</italic> infections [<xref ref-type="bibr" rid="B8">8</xref>]. Eradication of <italic>HP</italic> can effectively control the disease progression associated with <italic>HP</italic> infection and is the most controllable measure to reduce the risk of gastric cancer [<xref ref-type="bibr" rid="B9">9</xref>]. There have been some investigations and analyses focusing on the current status of <italic>HP</italic> infection in different regions of China, but there is a lack of comparative studies on the current status and differences between <italic>HP</italic> infection in highland areas and plains. In this study, we used a multicenter cross-sectional study to explore and compare the current status and differences of <italic>HP</italic> infection in the highland and plains areas, to provide data for the prevention and control of HP infection in the highland and plains areas, and guide how to formulate public health policies and preventive and control strategies targeting. <italic>HP</italic> infection by local conditions, to prevent <italic>HP</italic> infection-related diseases and to improve the level of health.</p>
      <p>The global prevalence of <italic>HP</italic> in adults between 2011 and 2022 is 43.1%, with similar rates for men and women. However, there is regional variability in the infection rate, with the Middle East having the highest rate of 56.1%, followed by Asia with 53.3%. The overall <italic>HP</italic> infection rate in our population is higher than the global rate, 46.7%, and is higher in rural than in urban areas, with the highest rate (&gt;50%) in people aged 30 - 60 years. The results of the urea breath test showed that the prevalence of <italic>HP</italic> infection in the medical checkup population in different regions ranged from 25.8% to 38.82%, indicating that it is necessary to actively carry out <italic>HP</italic> screening in the medical checkup population and strengthen the post-test intervention and management, which can help to reduce the risk of gastric cancer in this opportunistic population, and it is one of the most important strategies for gastric cancer prevention and control.</p>
    </sec>
    <sec id="sec2">
      <title>2. Methods</title>
      <sec id="sec2dot1">
        <title>2.1. Study Population</title>
        <p>The study was a multi-center cross-sectional study and the survey was conducted using a convenience sampling method. Health check-ups who completed <sup>13</sup>C-UBT examination at the Health Management Center of Deyang People’s Hospital and the Health Management Center of Ruoergai County People’s Hospital from January 2023 to December 2023 were selected as the study subjects and completed basic information collection, physical examination, blood routine, biochemical indexes, and lipid indexes examination. Ethical approval for the study was granted by the Ethics Committee of the People’s Hospital of Deyang City (Ethical Review Approval No. 2023-04-024-K01).</p>
      </sec>
      <sec id="sec2dot2">
        <title>2.2. Inclusion and Exclusion Criteria</title>
        <p><bold>Inclusion criteria:</bold>1) No related medications such as proton pump inhibitors, antimicrobials, or nonsteroidal anti-inflammatory drugs have been taken in the last 4 weeks; 2) Have not been diagnosed with a digestive system-related disease or undergone surgery on the gastrointestinal area within the last 1 year; 3) Obtaining informed consent and signing an informed consent form from the medical examiner himself/herself and his/her family.</p>
        <p><bold>Exclusion Criteria:</bold>1) Those who have had previous <italic>HP</italic> infections; 2) Received <italic>HP</italic> eradication therapy in the previous 3 months; 3) Those who cannot perform the 13-C urea breath test; 4) Familial hypercholesterolemia and hypertriglyceridemia.</p>
      </sec>
      <sec id="sec2dot3">
        <title>
          2.3.
          <italic>Helicobacter pylori</italic>
          Seropositivity
        </title>
        <p>The subjects were fasted for at least 2 h before the examination, and 0 min of expiratory breath was collected before taking a urea capsule (containing 75 mg of 13C-urea) with room-temperature drinking water, and the expiratory breath was collected for 30 min after the drug was taken. Connect the 2 breath sample bags to the HY-IREXB plus 13C breathalyzer (Beijing Huagan Anbang Science and Technology Co., Ltd.) and perform the 13C-urea breath test. Results Judgement: DOB values ≥4.0 were defined as positive for <italic>HP</italic> infection and &lt;4.0 as negative for <italic>HP</italic> infection.</p>
      </sec>
      <sec id="sec2dot4">
        <title>2.4. Data Collection and Measurement</title>
        <p>1) Basic information collection</p>
        <p>Basic information was collected using a uniform, self-administered questionnaire for health check-up populations in the Plateau and Plains, including gender, age, education level, smoking history, alcohol consumption history, dining patterns, and family history. </p>
        <p>Body Mass Index (BMI) = weight (kg)/height (m<sup>2</sup>).</p>
        <p>2) Collection of blood indicators</p>
        <p>Biochemical indicators: Including triglycerides（TG）, total cholesterol（TC）low density lipoprotein (LDL) low density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), alanine transferase (ALT), aspartate amino transferase (AST), total bilirubin (TB), fasting plasma glucose (FPG), uric acid (UA), urea nitrogen (UREA), creatinine (CREA). All tests were performed using a Beckman 5800 fully automated biochemical analyzer (Beckman Coulter Co., Ltd., USA) and Sysmex XE-2100 analyzer (Sysmex Corporation, Japan).</p>
      </sec>
      <sec id="sec2dot5">
        <title>2.5. Decision Criteria</title>
        <p>1) Body mass index: According to the relevant guidelines [<xref ref-type="bibr" rid="B10">10</xref>][<xref ref-type="bibr" rid="B11">11</xref>], 4 groups of body mass were categorized as lean, normal, overweight and obese according to BMI &lt;18.5, 18.5~, 24.0~ and ≥28.0 kg/m<sup>2</sup>.</p>
        <p>2) Blood biochemistry and lipid levels: The normal ranges for alanine aminotransferase, total bilirubin, direct bilirubin, albumin, aspartate aminotransferase, total cholesterol, triglycerides, low-density lipoprotein cholesterol, uric acid, creatinine, fasting blood glucose, and urea nitrogen were 7 - 40 U/L, 0 - 21 umol/L, 0 - 5.1 umol/L, 40 - 55 g/L, 13 - 35 U/L, 0 - 5.18 mmol/L, 0 - 1.7 mmol/L, 0 - 3.3 mmol/L, 155 - 357 umol/L, 41 - 81 umol/L, 3.9 - 6.1 mmol/L, 3.1 - 8.8 mmol/L。Classification of normal/abnormal based on the range of normal values.</p>
      </sec>
      <sec id="sec2dot6">
        <title>2.6. Quality Control</title>
        <p>To ensure the accuracy and reliability of the results, strict quality control measures were implemented during the data collection and analysis process. 13CUBT operations are performed by professionally trained technicians to ensure standardization of testing. All biochemical tests are performed in a certified laboratory using standard operating procedures and calibrated equipment. Data cleaning and validation were performed before data entry and statistical analysis to ensure the accuracy of the analysis.</p>
      </sec>
      <sec id="sec2dot7">
        <title>2.7. Statistical Analysis</title>
        <p>Data analysis was performed using SPSS 26.0 software. Before performing statistical tests on the data, the normality of the data was first tested using the Kolmogorov-Smirnov test. For measures that conformed to a normal distribution, independent samples t-tests were used for between-group comparisons. Non-parametric tests (e.g., Mann-Whitney U test) were used for measures that did not fit a normal distribution. Count data were compared using the <italic>χ</italic><sup>2</sup> test. All statistical tests for normally distributed information are described using mean ± standard deviation, and non-normally distributed measures are expressed as median and quartiles [M (P25, P75)]. P &lt; 0.05 was considered a statistically significant difference.</p>
      </sec>
    </sec>
    <sec id="sec3">
      <title>3. Results</title>
      <sec id="sec3dot1">
        <title>3.1. Participants’ Baseline Characterization</title>
        <p>This study included 260 cases of health checkups in the highland area and 10,972 cases of health checkups in the plains area. There were no statistically significant differences between the plateau and the plains in terms of family history, urea, creatinine, and albumin levels (all P &gt; 0.05). The average age of the highland residents was (39.33 ± 12.69) years, which was lower than the (44.05 ± 12.38) years of the plains residents (P &lt; 0.05). The proportion of highly educated highland residents was significantly lower than that of Han Chinese residents, and the proportion of smokers, non-drinkers, non-exercisers, eating out, was significantly higher than that of plains residents, and the differences were all statistically significant (P &lt; 0.05), as shown in <bold>Table 1</bold>.</p>
        <p>Table 1. Comparison of general information between the highland group and the plains group.</p>
        <table-wrap id="tbl1">
          <label>Table 1</label>
          <table>
            <tbody>
              <tr>
                <td>Variable</td>
                <td>Plains group (n = 10,972)</td>
                <td>Plateau group (n = 260)</td>
                <td>P value</td>
              </tr>
              <tr>
                <td>Sex, n (%)</td>
                <td>
                </td>
                <td>
                </td>
                <td>&lt;0.001</td>
              </tr>
              <tr>
                <td>Male</td>
                <td>6211 (56.6%)</td>
                <td>130 (50.0%)</td>
                <td>
                </td>
              </tr>
              <tr>
                <td>Female</td>
                <td>4761 (43.4%)</td>
                <td>130 (50.0%)</td>
                <td>
                </td>
              </tr>
              <tr>
                <td>Age, mean ± SD</td>
                <td>44.05 ±12.38</td>
                <td>39.33±12.69</td>
                <td>&lt;0.001</td>
              </tr>
              <tr>
                <td>Educational levels, n (%)</td>
                <td>
                </td>
                <td>
                </td>
                <td>&lt;0.001</td>
              </tr>
              <tr>
                <td>Junior high school or below</td>
                <td>17 (0.2%)</td>
                <td>4 (1.5%)</td>
                <td>
                </td>
              </tr>
              <tr>
                <td>High school</td>
                <td>2588 (23.6%)</td>
                <td>68 (26.2%)</td>
                <td>
                </td>
              </tr>
              <tr>
                <td>College or above</td>
                <td>8367 (76.3%)</td>
                <td>188 (72.3%)</td>
                <td>
                </td>
              </tr>
              <tr>
                <td>
                  BMI
                  <sup>a</sup>
                </td>
                <td>
                </td>
                <td>
                </td>
                <td>&lt;0.001</td>
              </tr>
              <tr>
                <td>Undernutrition (&lt;18)</td>
                <td>2163 (20.0%)</td>
                <td>14 (5.4%)</td>
                <td>
                </td>
              </tr>
              <tr>
                <td>Normal (18.5 - 23.9)</td>
                <td>4289 (39.7%)</td>
                <td>125 (48.4%)</td>
                <td>
                </td>
              </tr>
              <tr>
                <td>Overweight (25 - 30)</td>
                <td>3246 (30.0%)</td>
                <td>91 (35.3%)</td>
                <td>
                </td>
              </tr>
              <tr>
                <td>Obese (30+)</td>
                <td>1112 (10.3%)</td>
                <td>28 (10.9%)</td>
                <td>
                </td>
              </tr>
              <tr>
                <td>Smoking, n (%)</td>
                <td>
                </td>
                <td>
                </td>
                <td>0.006</td>
              </tr>
              <tr>
                <td>Never</td>
                <td>8393 (76.5%)</td>
                <td>144 (55.4%)</td>
                <td>
                </td>
              </tr>
              <tr>
                <td>Occasional smoking</td>
                <td>696 (6.3%)</td>
                <td>53 (20.4%)</td>
                <td>
                </td>
              </tr>
              <tr>
                <td>Smoker</td>
                <td>1883 (17.2%)</td>
                <td>63 (24.2%)</td>
                <td>
                </td>
              </tr>
              <tr>
                <td>Drinking, n (%)</td>
                <td>
                </td>
                <td>
                </td>
                <td>&lt;0.001</td>
              </tr>
              <tr>
                <td>Never</td>
                <td>5960 (54.3%)</td>
                <td>174 (66.9%)</td>
                <td>
                </td>
              </tr>
              <tr>
                <td>Occasional alcohol consumption</td>
                <td>3514 (32.0%)</td>
                <td>51 (19.6%)</td>
                <td>
                </td>
              </tr>
              <tr>
                <td>Drinker</td>
                <td>1498 (13.7%)</td>
                <td>35 (13.5%)</td>
                <td>
                </td>
              </tr>
              <tr>
                <td>Physical activity, n (%)</td>
                <td>
                </td>
                <td>
                </td>
                <td>0.021</td>
              </tr>
              <tr>
                <td>&lt;150 min/week</td>
                <td>9259 (97.5%)</td>
                <td>233 (89.6%)</td>
                <td>
                </td>
              </tr>
              <tr>
                <td>≥150 min/week</td>
                <td>1713 (15.6%)</td>
                <td>27 (10.4%)</td>
                <td>
                </td>
              </tr>
              <tr>
                <td>Dine way, n (%)</td>
                <td>
                </td>
                <td>
                </td>
                <td>&lt;0.001</td>
              </tr>
              <tr>
                <td>Eat at home</td>
                <td>4390 (40.0%)</td>
                <td>148 (756.9%)</td>
                <td>
                </td>
              </tr>
              <tr>
                <td>Eat at cafeteria</td>
                <td>4729 (43.1%)</td>
                <td>46 (17.7%)</td>
                <td>
                </td>
              </tr>
              <tr>
                <td>Eat at restaurant</td>
                <td>1853 (16.9%)</td>
                <td>66 (25.4%)</td>
                <td>
                </td>
              </tr>
              <tr>
                <td>Family history, n (%)</td>
                <td>
                </td>
                <td>
                </td>
                <td>0.080</td>
              </tr>
              <tr>
                <td>No</td>
                <td>7392 (67.4%)</td>
                <td>158 (60.8%)</td>
                <td>
                </td>
              </tr>
              <tr>
                <td>Yes</td>
                <td>3580 (32.6%)</td>
                <td>102 (39.2%)</td>
                <td>
                </td>
              </tr>
              <tr>
                <td>Urea nitrogen, M (P25, P75)</td>
                <td>5.25 (4.43, 6.22)</td>
                <td>5.19 (4.49, 6.09)</td>
                <td>0.909</td>
              </tr>
              <tr>
                <td>Creatinine, M (P25, P75)</td>
                <td>70.90 (61.10, 78.50)</td>
                <td>69.80 (60.03, 81.78)</td>
                <td>0.665</td>
              </tr>
              <tr>
                <td>Uric acid, M (P25, P75)</td>
                <td>356. 80 (293.5, 425.7)</td>
                <td>317.75 (271.45, 386.25)</td>
                <td>&lt;0.001</td>
              </tr>
              <tr>
                <td>Fasting blood glucose, M (P25, P75)</td>
                <td>4.96 (4.62, 5.39)</td>
                <td>5.05 (4.78, 5.42)</td>
                <td>0.003</td>
              </tr>
              <tr>
                <td>Total cholesterol, M (P25, P75)</td>
                <td>5.30 (4.56, 6.98)</td>
                <td>5.03 (4.34, 5.60)</td>
                <td>&lt;0.001</td>
              </tr>
              <tr>
                <td>Triglycerides, M (P25, P75)</td>
                <td>1.70 (1.05, 5.29)</td>
                <td>1.30 (0.97, 1.90)</td>
                <td>&lt;0.001</td>
              </tr>
              <tr>
                <td>Low-density lipoprotein cholesterol, M (P25, P75)</td>
                <td>3.19 (2.52, 4.55)</td>
                <td>2.90 (2.37, 3.43)</td>
                <td>&lt;0.001</td>
              </tr>
              <tr>
                <td>High-density lipoprotein cholesterol, M (P25, P75)</td>
                <td>1.47 (1.17, 2.18)</td>
                <td>1.34 (1.11, 1.60)</td>
                <td>&lt;0.001</td>
              </tr>
              <tr>
                <td>Albumin, M (P25, P75)</td>
                <td>44.40 (27.00, 47.00)</td>
                <td>43.60 (42.63, 45.20)</td>
                <td>0.409</td>
              </tr>
              <tr>
                <td>Alanine aminotransferase, M (P25, P75)</td>
                <td>17.00 (9.00, 27.00)</td>
                <td>21.00 (15.00, 33.00)</td>
                <td>&lt;0.001</td>
              </tr>
              <tr>
                <td>Glutathione aminotransferase, M (P25, P75)</td>
                <td>20.00 (14.00, 25.00)</td>
                <td>21.00 (17.00, 25.00)</td>
                <td>&lt;0.001</td>
              </tr>
              <tr>
                <td>Total bilirubin, M (P25, P75)</td>
                <td>12.40 (7.30, 16.70)</td>
                <td>21.07 (16.53, 26.96)</td>
                <td>&lt;0.001</td>
              </tr>
              <tr>
                <td>Direct bilirubin, M (P25, P75)</td>
                <td>3.70 (2.90, 4.90)</td>
                <td>2.14 (1.38, 3.10)</td>
                <td>&lt;0.001</td>
              </tr>
              <tr>
                <td>
                  <italic>HP</italic>
                  infection, n (%)
                </td>
                <td>3253 (29.8%)</td>
                <td>144 (55.4%)</td>
                <td>&lt;0.001</td>
              </tr>
            </tbody>
          </table>
        </table-wrap>
      </sec>
      <sec id="sec3dot2">
        <title>
          3.2.
          <italic>HP</italic>
          Infection
        </title>
        <p>The number of positives was 144 out of 260 health checkups in the highlands, a detection rate of 55.4%. The number of positive cases was 3253 out of 10,972 cases of health checkups in the plains, with a detection rate of 29.8%, a statistically significant difference (P &lt; 0.05). Among the <italic>HP</italic>-infected subjects, the differences between the highland and plains populations were statistically significant in terms of education, BMI, smoking history, dining patterns, uric acid, TC, TG, LDL-C, ALT, AST, total bilirubin, and direct bilirubin. The proportion of those with low education, overweight and obesity ratio, smoking history, eating out, and total bilirubin abnormality was higher than that of those who had health checkups in the plain area, and the proportion of those with abnormality in TC, TG, LDL-C, ALT, AST, and direct bilirubin was lower than that of those who had health checkups in the plain area, and the difference was statistically significant (P &lt; 0.05). There was no statistically significant difference between the two groups in the percentage of gender, age, history of alcohol consumption, family history, urea, creatinine, and fasting blood glucose abnormalities (P &gt; 0.05), see <bold>Table 2</bold>.</p>
        <p>Table 2. Comparative analysis of clinical data of <italic>HP</italic>-infected patients in highland group and plains group.</p>
        <table-wrap id="tbl2">
          <label>Table 2</label>
          <table>
            <tbody>
              <tr>
                <td>Variable</td>
                <td>Plains group (n = 3253)</td>
                <td>Plateau group (n = 144)</td>
                <td>P value</td>
              </tr>
              <tr>
                <td>Sex, n (%)</td>
                <td>
                </td>
                <td>
                </td>
                <td>0.053</td>
              </tr>
              <tr>
                <td>Male</td>
                <td>2001 (61.5%)</td>
                <td>77 (53.5%)</td>
                <td>
                </td>
              </tr>
              <tr>
                <td>Female</td>
                <td>1252 (38.5%)</td>
                <td>67 (46.5%)</td>
                <td>
                </td>
              </tr>
              <tr>
                <td>Age (mean ± SD)</td>
                <td>
                </td>
                <td>
                </td>
                <td>0.093</td>
              </tr>
              <tr>
                <td>&lt;60 years</td>
                <td>2863 (88.0%)</td>
                <td>120 (83.3%)</td>
                <td>
                </td>
              </tr>
              <tr>
                <td>≥60 years</td>
                <td>390 (12.0%)</td>
                <td>24 (16.7%)</td>
                <td>
                </td>
              </tr>
              <tr>
                <td>Educational levels</td>
                <td>
                </td>
                <td>
                </td>
                <td>&lt;0.001</td>
              </tr>
              <tr>
                <td>Junior high school or below</td>
                <td>3 (0.1%)</td>
                <td>3 (2.1%)</td>
                <td>
                </td>
              </tr>
              <tr>
                <td>High school</td>
                <td>742 (22.8%)</td>
                <td>37 (25.7%)</td>
                <td>
                </td>
              </tr>
              <tr>
                <td>College or above</td>
                <td>2508 (77.1%)</td>
                <td>104 (72.2%)</td>
                <td>
                </td>
              </tr>
              <tr>
                <td>BMI</td>
                <td>
                </td>
                <td>
                </td>
                <td>0.001</td>
              </tr>
              <tr>
                <td>Undernutrition (&lt;18)</td>
                <td>662 20.6%)</td>
                <td>11 (7.7%)</td>
                <td>
                </td>
              </tr>
              <tr>
                <td>Normal (18.5 - 23.9)</td>
                <td>1126 (35.1%)</td>
                <td>58 (40.8%)</td>
                <td>
                </td>
              </tr>
              <tr>
                <td>Overweight (25 - 30)</td>
                <td>1047 (32.6%)</td>
                <td>60 (42.3%)</td>
                <td>
                </td>
              </tr>
              <tr>
                <td>Obese (30+)</td>
                <td>372 (11.6%)</td>
                <td>13 (9.2%)</td>
                <td>
                </td>
              </tr>
              <tr>
                <td>Smoking, n (%)</td>
                <td>
                </td>
                <td>
                </td>
                <td>&lt;0.001</td>
              </tr>
              <tr>
                <td>Never</td>
                <td>2362 (72.6%)</td>
                <td>82 (56.9%)</td>
                <td>
                </td>
              </tr>
              <tr>
                <td>Occasional smoking</td>
                <td>227 (7.0%)</td>
                <td>25 (17.4%)</td>
                <td>
                </td>
              </tr>
              <tr>
                <td>Smoker</td>
                <td>664 (20.4%)</td>
                <td>37 (25.7%)</td>
                <td>
                </td>
              </tr>
              <tr>
                <td>Drinking, n (%)</td>
                <td>
                </td>
                <td>
                </td>
                <td>0.060</td>
              </tr>
              <tr>
                <td>Never</td>
                <td>1760 (54.0%)</td>
                <td>94 (65.3%)</td>
                <td>
                </td>
              </tr>
              <tr>
                <td>Occasional alcohol consumption</td>
                <td>1007 (31.0%)</td>
                <td>33 (22.9%)</td>
                <td>
                </td>
              </tr>
              <tr>
                <td>Drinker</td>
                <td>486 (15.0%)</td>
                <td>17 (11.8%)</td>
                <td>
                </td>
              </tr>
              <tr>
                <td>Dine way, n (%)</td>
                <td>
                </td>
                <td>
                </td>
                <td>&lt;0.001</td>
              </tr>
              <tr>
                <td>Eat at home</td>
                <td>1323 (40.7%)</td>
                <td>67 (46.5%)</td>
                <td>
                </td>
              </tr>
              <tr>
                <td>Eat at cafeteria</td>
                <td>1405 (43.2%)</td>
                <td>26 (18.1%)</td>
                <td>
                </td>
              </tr>
              <tr>
                <td>Eat at restaurant</td>
                <td>525 (16.1%)</td>
                <td>51 (35.4%)</td>
                <td>
                </td>
              </tr>
              <tr>
                <td>Family history, n (%)</td>
                <td>
                </td>
                <td>
                </td>
                <td>0.092</td>
              </tr>
              <tr>
                <td>No</td>
                <td>1641 (50.4%)</td>
                <td>86 (59.7%)</td>
                <td>
                </td>
              </tr>
              <tr>
                <td>Yes</td>
                <td>1612 (49.6%)</td>
                <td>58 (40.3%)</td>
                <td>
                </td>
              </tr>
              <tr>
                <td>Urea nitrogen (mmol/L, n %)</td>
                <td>
                </td>
                <td>
                </td>
                <td>0.636</td>
              </tr>
              <tr>
                <td>Normal</td>
                <td>3120 (96.6%)</td>
                <td>138 (95.8%)</td>
                <td>
                </td>
              </tr>
              <tr>
                <td>Abnormal</td>
                <td>110 (3.4%)</td>
                <td>6 (4.2%)</td>
                <td>
                </td>
              </tr>
              <tr>
                <td>Creatinine (umol /L, n %)</td>
                <td>
                </td>
                <td>
                </td>
                <td>0.193</td>
              </tr>
              <tr>
                <td>Normal</td>
                <td>2569 (80.5%)</td>
                <td>107 (75.9%)</td>
                <td>
                </td>
              </tr>
              <tr>
                <td>Abnormal</td>
                <td>621 (19.5%)</td>
                <td>34 (24.1%)</td>
                <td>
                </td>
              </tr>
              <tr>
                <td>Uric acid (umol/L, n %)</td>
                <td>
                </td>
                <td>
                </td>
                <td>&lt;0.001</td>
              </tr>
              <tr>
                <td>Normal</td>
                <td>1569 (48.4%)</td>
                <td>92 (63.9%)</td>
                <td>
                </td>
              </tr>
              <tr>
                <td>Abnormal</td>
                <td>1670 (51.6%)</td>
                <td>52 (36.1%)</td>
                <td>
                </td>
              </tr>
              <tr>
                <td>Fasting blood glucose (mmol/L, n %)</td>
                <td>
                </td>
                <td>
                </td>
                <td>0.889</td>
              </tr>
              <tr>
                <td>Normal</td>
                <td>2865 (89.4%)</td>
                <td>128 (90.1%)</td>
                <td>
                </td>
              </tr>
              <tr>
                <td>Abnormal</td>
                <td>340 (10.6%)</td>
                <td>14 (9.9%)</td>
                <td>
                </td>
              </tr>
              <tr>
                <td>Total cholesterol (mmol/L)</td>
                <td>
                </td>
                <td>
                </td>
                <td>0.013</td>
              </tr>
              <tr>
                <td>Normal</td>
                <td>1482 (45.6%)</td>
                <td>81 (56.3%)</td>
                <td>
                </td>
              </tr>
              <tr>
                <td>Abnormal</td>
                <td>1771 (54.4%)</td>
                <td>63 (43.8%)</td>
                <td>
                </td>
              </tr>
              <tr>
                <td>Triglycerides (mmol/L, n %)</td>
                <td>
                </td>
                <td>
                </td>
                <td>&lt;0.001</td>
              </tr>
              <tr>
                <td>Normal</td>
                <td>1606 (50.6%)</td>
                <td>101 (73.2%)</td>
                <td>
                </td>
              </tr>
              <tr>
                <td>Abnormal</td>
                <td>1567 (49.4%)</td>
                <td>37 (26.8%)</td>
                <td>
                </td>
              </tr>
              <tr>
                <td>Low-density lipoprotein cholesterol (mmol/L, n %)</td>
                <td>
                </td>
                <td>
                </td>
                <td>&lt;0.001</td>
              </tr>
              <tr>
                <td>Normal</td>
                <td>1732 (54.8%)</td>
                <td>97 (70.8%)</td>
                <td>
                </td>
              </tr>
              <tr>
                <td>Abnormal</td>
                <td>1427 (45.2%)</td>
                <td>40 (29.2%)</td>
                <td>
                </td>
              </tr>
              <tr>
                <td>Alanine aminotransferase (U/L, n %)</td>
                <td>
                </td>
                <td>
                </td>
                <td>0.005</td>
              </tr>
              <tr>
                <td>Normal</td>
                <td>2149 (67.1%)</td>
                <td>113 (78.5%)</td>
                <td>
                </td>
              </tr>
              <tr>
                <td>Abnormal</td>
                <td>1052 (32.9%)</td>
                <td>31 (21.5%)</td>
                <td>
                </td>
              </tr>
              <tr>
                <td>Glutathione aminotransferase (U/L, n %)</td>
                <td>
                </td>
                <td>
                </td>
                <td>&lt;0.001</td>
              </tr>
              <tr>
                <td>Normal</td>
                <td>2244 (69.0%)</td>
                <td>129 (89.6%)</td>
                <td>
                </td>
              </tr>
              <tr>
                <td>Abnormal</td>
                <td>1009 (31.0%)</td>
                <td>15 (10.4%)</td>
                <td>
                </td>
              </tr>
              <tr>
                <td>Total bilirubin (umol/L, n %)</td>
                <td>
                </td>
                <td>
                </td>
                <td>&lt;0.001</td>
              </tr>
              <tr>
                <td>Normal</td>
                <td>2888 (90.4%)</td>
                <td>77 (55.00%)</td>
                <td>
                </td>
              </tr>
              <tr>
                <td>Abnormal</td>
                <td>305 (9.6%)</td>
                <td>63 (45.00%)</td>
                <td>
                </td>
              </tr>
              <tr>
                <td>Direct bilirubin (umol/L, n %)</td>
                <td>
                </td>
                <td>
                </td>
                <td>&lt;0.001</td>
              </tr>
              <tr>
                <td>Normal</td>
                <td>2547 (78.3%)</td>
                <td>135 (95.1%)</td>
                <td>
                </td>
              </tr>
              <tr>
                <td>Abnormal</td>
                <td>705 (21.7%)</td>
                <td>7 (4.9%)</td>
                <td>
                </td>
              </tr>
            </tbody>
          </table>
        </table-wrap>
      </sec>
    </sec>
    <sec id="sec4">
      <title>4. Discussion</title>
      <p>This study is the first to compare the current status and differential characteristics of <italic>HP</italic> infection in a healthy physical examination population in highland and plains areas. The survey included 260 cases of health checkups in the highlands and 10,972 cases in the plains, and the results showed that the prevalence of <italic>HP</italic> infection was significantly higher in the highlands than in the plains. <italic>HP</italic> infection is influenced by many factors such as environment, cultural level, and living habits. People who live at high altitudes, have low levels of education, and eat out more frequently are usually more susceptible to <italic>HP</italic> infection than the rest of the population [<xref ref-type="bibr" rid="B7">7</xref>][<xref ref-type="bibr" rid="B12">12</xref>]. The results of this study showed that the <italic>HP</italic> infection rate in the health checkup population in the plateau region was 55.4%, which was lower than the national average infection level, which may be related to the improved hygiene and health awareness of the local population as well as the small sample size of this survey in the plateau region. Cui Ying <italic>et al</italic><italic>.</italic> [<xref ref-type="bibr" rid="B13">13</xref>] showed that the <italic>HP</italic> prevalence rate in the health checkup population in the plateau region was 62.47%, which was slightly higher than the average of this study and China, which may be related to the higher proportion of patients included in the study who frequently used pickled or barbecued foods and had a history of chronic gastric disease.</p>
      <p>In addition, some researchers have pointed out that the high rates of <italic>HP</italic> infection and gastric cancer among plateau residents are not only due to the backwardness of health and economy, but may also be related to the environmental characteristics of the plateau [<xref ref-type="bibr" rid="B14">14</xref>]. Plateau populations living in alpine and hypoxic environments may undergo a series of adaptive changes in their respiratory system, cardiovascular system, and metabolic characteristics [<xref ref-type="bibr" rid="B15">15</xref>]. A survey comparing the prevalence of <italic>HP</italic> infection among residents at different altitudes showed that the prevalence of <italic>HP</italic> infection among residents living at high altitudes was 68.67%, which was significantly higher than that of 57.33% among residents who moved to low altitudes [<xref ref-type="bibr" rid="B16">16</xref>]. This is consistent with the results of this study. A study investigating patients with digestive symptoms in high-altitude regions of India found a higher prevalence of <italic>H</italic><italic>P</italic> infection through histopathology and endoscopy [<xref ref-type="bibr" rid="B17">17</xref>]. In addition, a recent study indicated that high-altitude hypoxia exacerbates gastric mucosal inflammation and injury by enhancing oxidative stress and inflammatory response induced by <italic>HP</italic> infection [<xref ref-type="bibr" rid="B18">18</xref>]. However, a previous study showed that high altitude and the colder climate do not influence on the prevalence of <italic>HP</italic> in Saudi nationals sharing similar genetic and cultural habits, which is possibly related to sample size, and differences between study areas [<xref ref-type="bibr" rid="B19">19</xref>]. The causal relationship between altitude and HP infection needs to be further investigated.</p>
      <p>In the <italic>HP</italic>-infected population, the percentage of overweight or obese group was higher in the plateau region than in the plains, which may be related to the dietary habits and lifestyle in the plateau region. It is also associated with the role of the intestinal immune system in prompting the body to secrete inflammatory factors and increase insulin resistance after <italic>HP</italic> infection. The recent meta-analysis results showed that there was a positive correlation between the risk of <italic>H</italic><italic>P</italic> infection and the prevalence of obesity development [<xref ref-type="bibr" rid="B20">20</xref>]. <italic>H</italic><italic>P</italic>infection triggers the release of the orexigenic hormone, ghrelin, which regulates the appetite [<xref ref-type="bibr" rid="B21">21</xref>]. Obese/overweight individuals have been shown to exhibit reduced circulating levels of ghrelin, indicating a potential association between ghrelin and obesity [<xref ref-type="bibr" rid="B22">22</xref>]. In addition, <italic>H</italic><italic>P-</italic>positive individuals have been shown to exhibit reduced serum levels of leptin [<xref ref-type="bibr" rid="B23">23</xref>][<xref ref-type="bibr" rid="B24">24</xref>]. Reduced leptin levels induce appetite, which leads to overfeeding, resulting in overweight and obesity [<xref ref-type="bibr" rid="B25">25</xref>]. However, in a meta-analysis, previous studies were found to be geographically diverse, with more retrospective studies and fewer observational studies, and many uncontrollable confounding factors may be involved in the process of obesity development and <italic>HP</italic> infection [<xref ref-type="bibr" rid="B26">26</xref>], and there is still a need for large cohort studies and large-sample randomized controlled trials to study the relationship between obesity and <italic>HP</italic>. </p>
      <p>Results are inconsistent between studies regarding the possible relationship between <italic>H</italic><italic>P</italic> infection and smoking. No relationship between <italic>H</italic><italic>P</italic> infection and smoking was found in the majority of cases. In this study, the smoking rate of <italic>HP</italic>-infected patients was higher in the plateau than in the plains, which was consistent with previous studies [<xref ref-type="bibr" rid="B27">27</xref>]. Features of high-altitude environments allow hypoxia, energy depletion, and tissue acidosis in localized tissues, which may damage intestinal epithelial cells and disrupt tight junction protein complexes, leading to intestinal barrier dysfunction [<xref ref-type="bibr" rid="B28">28</xref>]. In this environment accompanied by tobacco and alcohol addiction, gastric acid, and duodenal bicarbonate secretion increased, damage to the gastric mucosal barrier. Furthermore, Nicotine appears to enhance gastric invasive factors (e.g., gastric acid and pepsin secretion, duodenal gastric reflux, and free radical production) and weaken mucosal defenses (e.g., prosta-glandin synthesis, mucus production, and epidermal growth factor secretion), which may enhance colonization following <italic>H. pylori</italic> exposure [<xref ref-type="bibr" rid="B29">29</xref>]. Although the available data were insufficient to examine the causal relationships between smoking and the risk of <italic>HP</italic> infection, smoking cessation should be advocated to reduce <italic>H</italic><italic>P</italic> infection; in the meantime, it is necessary to make individualized health management and intervention programs for people who smoke and are infected with <italic>HP</italic> to reduce the infection and prevalence, which in turn effectively reduces the incidence of secondary diseases, such as gastric ulcers, and gastric cancer.</p>
      <p>In this study, it has been shown [<xref ref-type="bibr" rid="B30">30</xref>] that alcohol consumption destroys the barrier effect of gastric mucosa and triggers gastrointestinal diseases, and that <italic>HP</italic> infection and long-term alcohol consumption lead to the inhibition of IL10-induced CD8+ cell dysfunction and the inhibition of NKX6.3 expression-induced gastric carcinogenesis. However, the study did not find any difference between <italic>HP</italic> infection individuals from the plateau and the plains, which may be related to the small number of alcohol drinkers included in the study. </p>
      <p>This study showed that the serum total bilirubin was significantly higher in the plateau than in the plains, but direct bilirubin lower than in the plains, and this study is similar to the findings of Zeng <italic>et al</italic><italic>.</italic> [<xref ref-type="bibr" rid="B31">31</xref>], which showed that the percentage of total bilirubin abnormalities in plateau officers and soldiers at altitudes &gt;3000 m was higher than that in the population at altitudes &lt;1000 m. The increase of bilirubin is mainly due to the hypoxia-induced increase in secretion of erythropoietin after the organism enters the plateau, driving the compensatory mass production of red blood cells and hemoglobin, and the corresponding increase in senescence and destruction of red blood cells, and a large amount of hemoglobin is converted into indirect bilirubin, which is more than the processing capacity of the liver, and it can’t be completely converted into direct bilirubin, so the level of serum total bilirubin is elevated [<xref ref-type="bibr" rid="B32">32</xref>]. In addition, TBIL and DBIL in the Han population were significantly higher than those in the Xizang’s population for 3 consecutive years. Even the average level of TBIL in the Han nationality has exceeded the upper limit of the normal reference value for three consecutive years, which shows that the metabolic burden of the liver is heavier in the Han population at extremely high altitudes [<xref ref-type="bibr" rid="B33">33</xref>]. Studies have shown that <italic>H</italic><italic>P</italic> infection may be associated with decreased bilirubin concentrations within the reference range [<xref ref-type="bibr" rid="B34">34</xref>]. The possible mechanism is that <italic>H</italic><italic>P</italic> itself acts as an immunogen, and its virulence factor induces the recruitment of immune cells, releasing a large number of cytokines that can function far from the gastric mucosa, such as IL-6, IL-8, and tumor necrosis factor-alpha, which inhibit the activity of heme hydroxylase and reduce bilirubin production [<xref ref-type="bibr" rid="B35">35</xref>]. Furthermore, <italic>H</italic><italic>P</italic> infection has been shown to result in chronic inflammation and influence bile reflux [<xref ref-type="bibr" rid="B36">36</xref>], which may at least in part explain the bilirubin changes, but further research relating to possible mechanisms is required.</p>
      <p>In this study, the two groups of <italic>HP</italic>-infected patients also differed in TC, TG, LDL-C, ALT, and AST, which is related to the fact that chronic <italic>HP</italic> infection may affect lipid metabolism, stimulate the body to initiate systemic immune responses and inflammatory reactions and promote atherosclerosis [<xref ref-type="bibr" rid="B37">37</xref>][<xref ref-type="bibr" rid="B38">38</xref>]. The results of several studies at home and abroad have shown that TC, TG, and LDL-C levels are elevated in <italic>HP</italic>-infected patients, which is consistent with the results of this study [<xref ref-type="bibr" rid="B39">39</xref>]-[<xref ref-type="bibr" rid="B41">41</xref>].</p>
      <p>This study is the first to compare and analyze the <italic>HP</italic> infection status of health check-up populations in the plateau and plains based on multicenter real-world big data, providing strong data on ethnic and regional differences in <italic>HP</italic> infection in the plateau region. The shortcomings of the study are mainly in the following three areas. First, the sample size of the highland areas included in the survey was small and from a concentrated source, and a large-scale, multiregional sampling survey has yet to be organized to provide more convincing evidence. Second, the study population did not undergo gastroscopy, so it was not possible to assess the differences in the pathologic changes in the gastric mucosa of the <italic>HP</italic> infection population in the highlands and plains. Future studies could incorporate gastroscopy and histological examination to confirm <italic>HP</italic> infection and assess the severity of gastritis and other gastric lesions to provide a more complete picture of the disease burden. Thirdly, the populations sampled (health check-up attendees) might not accurately represent wider community <italic>HP</italic> infection rates. Therefore, large-scale, multiregional sampling surveys need to be organized to better explore the current status of <italic>HP</italic> infection. In summary, the rate of <italic>HP</italic> infection is higher in the population of health checkups in the plateau region, and the population in the plateau region mostly has lifestyle-related factors such as low educational level, high percentage of smoking, a large percentage of overweight or obesity, and high percentage of eating out. The prevention and control of <italic>HP</italic>-related infection factors should be strengthened in highland areas.</p>
    </sec>
  </body>
  <back>
    <ref-list>
      <title>References</title>
      <ref id="B1">
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