Figures
Abstract
This study aimed to analyze the influence of H. pylori infection on insulin resistance and metabolic syndrome (MS) by multivariate analysis of a community-based cohort study. From January 2013 to February 2014,811 subjects were enrolled in a community-based cohort study from the northeastern region of Taiwan. All subjects received a demographic survey and blood tests, including an H. pylori antibody test, liver biochemistry tests, lipid profiles, sugar/insulin levels for Homeostatic model assessment (HOMA-IR index), and measurements of adipokines and inflammatory cytokines. A total of 264 men and 547 women were included in this study. The mean age was 59.2 ± 12.7 years. Subjects seropositive for H. pylori antibodies exhibited higher rates of hypertension, an increased incidence of a HOMA-IR index > 2.5 and a higher level of tumor necrosis factor-α than those without H. pylori antibodies. We found a significant difference in the presence of H. pylori antibodies between subjects with MS and those without MS (76.7% vs. 53.7%, p = 0.007) among subjects < 50 y/o. A HOMA-IR index >2.5, H. pylori antibody presence and leptin were predictors for MS in subjects < 50 y/o. The estimated odds ratio of MS for a subject with H. pylori antibodies was 3.717 (95% CI = 1.086–12.719) times that of a subject without H. pylori antibodies. In addition, no difference in H. pylori antibody status was detected for MS prediction in subjects that were ≧ 50 y/o (p = 0.861). In conclusion, subjects with H. pylori antibodies had a higher incidence of a HOMA-IR >2.5 than those without H pylori antibodies. For subjects aged < 50 y/o, the H. pylori antibody was a predictor for MS.
Citation: Chen L-W, Chien C-Y, Yang K-J, Kuo S-F, Chen C-H, Chien R-N (2015) Helicobacter pylori Infection Increases Insulin Resistance and Metabolic Syndrome in Residents Younger than 50 Years Old: A Community-Based Study. PLoS ONE 10(5): e0128671. https://doi.org/10.1371/journal.pone.0128671
Academic Editor: Marta Letizia Hribal, University of Catanzaro Magna Graecia, ITALY
Received: November 19, 2014; Accepted: April 30, 2015; Published: May 28, 2015
Copyright: © 2015 Chen et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited
Data Availability: All relevant data are within the paper.
Funding: This study was supported by grants from Chang-Gung Memorial Hospital (No CMRPG2B0122 and CMRPG2B0172). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
Introduction
Helicobacter pylori (H. pylori) infection will induce chronic inflammation and immune responses in the stomach [1–3]. Some inflammatory cytokines and adipokines, such as tumor necrosis factor α (TNF-α) and leptin may be involved in this inflammation or immune response [4–9]. Patients with H. pylori infection have a lower serum fasting leptin level but a higher TNF-α value [7,9]. Past studies have revealed that a leptin deficiency and a high TNF-α level will induce insulin resistance (IR) [10–13]. IR and central obesity are the key mechanisms for developing metabolic syndrome (MS) [14]. The relationships between H. pylori infection and IR or MS have been reported by several investigations, including two large Japanese population studies and one meta-analysis study [15–20]. However, other investigations have found conflicting results [21,22]. Most studies did not include cytokine/adipokine data and used different MS criteria. The two most popular MS criteria are the National Cholesterol Education Program—Adult Treatment Panel III (NCEP-ATP III) and the International Diabetes Federation (IDF) criteria [23–26]. Because central obesity (visceral obesity) evaluation is an important element in an MS screening study, it is necessary to apply different waist circumference thresholds to different race/ethnicity groups [24,25,27]. The hypothesis of this study is that H. pylori infection induces inflammatory cytokines and adipokines, which result in IR and MS. The influence of H. pylori infection on IR and MS was prospectively studied in a community-based screening program using the NCEP-ATP III MS criteria. Serum inflammatory cytokines or adipokines, such as TNF-α, high sensitivity C-reactive proteins (HS-CRP), adiponectin and leptin, were examined for all enrolled subjects.
Materials and Methods
From August 2013 to February 2014, a community- based cohort study was performed in the Wanli, Ruifang and Anle districts in the north-eastern region of Taiwan. All subjects participated in a demographic survey, physical examination and blood tests. Waist circumference was measured at the midline between the lowest margin of the subcostal rib and the upper margin of the iliac crest. Body mass index (BMI) was measured as weight (kg) divided by height (meters) squared (kg/m2). Blood samples were collected from all participants after overnight fasting and were immediately (within four hours after collection) analyzed for complete blood cell count, biochemistry and antibody titers. Additional samples were transferred into a chilled tube, centrifuged immediately (4°C at 3000 rpm for 30 minutes) and stored at -80°C until assays for adiponectin, leptin and TNF-α were performed.
Subjects with systemic diseases, such as diabetes mellitus (DM), hypertension, hyperlipidemia or chronic kidney disease were recorded. A standardized questionnaire was administered to all subjects by a trained team of interviewers. Information obtained via the questionnaire included comprehensive alcohol consumption (amount, duration, and the AUDIT and CAGE questionnaires), smoking and chewing betel nut status, medication history (oral hypoglycemia agents, insulin injection, statins, herbal medicine, hormones, and antibiotics), family history, and physical activity (SF36 health survey),. Telephone calls for the past drug history of H. pylori eradication survey were performed following the serum IgG anti H. pylori test. This research was approved by the Institutional Review Board of the Chang-Gung Memorial Hospital (IRB No: 102-2827C, 103-2392C1). Written informed consent was obtained from all subjects before enrollment in this study.
H. pylori-specific immunoglobulin G (IgG) antibody
The IgG anti H. pylori titer was determined with a commercially available enzyme linked immunosorbent assay (Pyloriset Dry, Orion Diagnostica, Espoo, Finland). The rapid latex agglutination method was used to detect the H. pylori antibody. The local validation of Pyloriset Dry test had been done in the department of clinical pathology of our hospital. The sensitivity and specificity were around 95% and 82% respectively, which were very near the manufacturer’s instruction data (sensitivity 97%, specificity 85% and agreement 92%, respectively).
Adiponectin and leptin
The assays for adiponectin and leptin employed the quantitative sandwich enzyme immunoassay technique and were performed according to the manufacturer’s instructions (Human Total Adiponectin/Acrp30, BioVendor Research and Diagnostic system, Minneapolis, USA; Human Leptin ELISA, Clinical Range, BioVendor Laboratory Medicine, Karasek, Czech Republic).
Tumor necrosis factor alpha (TNF-α)
The TNF-α assay used a quantitative sandwich enzyme immunoassay technique and was performed according to the manufacturer’s instructions (Immunite 1000 LKNF1, Siemens Medical Solutions Diagnostics, Llanberis, UK)
Glycosylated hemoglobin (Hb A1c)
We used boronate affinity and high-performance liquid chromatography (HPLC) to analyze the percent of glycosylated hemoglobin in the blood samples. The detected range was 3.8~18.5% (Premier Hb9210, Trinity Biotech PLC, Kansas City, USA).
Homeostasis model assessment of insulin resistance (HOMA-IR)
The estimate of IR was determined by the HOMA score, which was calculated by the formula: [fasting plasma insulin (mU/L) × fasting plasma glucose (mmol/L)]/22.5. A high HOMA-IR score denotes low insulin sensitivity and IR [28]. Although there is no a standard normal range of HOMA-IR, the upper cut-off value of HOMA-IR has been proposed between 2.0 and 3.0 in different populations [18, 20, 22, 28, 29]. To avoid using an arbitrary cut-off value, this study applied three cut-off values of HOMA-IR index (2, 2.5 and 3) to evaluate IR.
Short Form-36 (SF-36)
The Taiwan version SF-36 questionnaire was applied for quality of life survey [30, 31]. SF-36 consists of eight sections with scaled scores, includes sections of vitality, physical functioning, bodily pain, general health perceptions, physical role functioning, emotional role functioning, social role functioning and mental health. Each scale is directly transformed into a 0–100 scale on the assumption that each question carries equal weight. The lower the score means the more disability. The higher the score mean the less disability. Two aggregate summary measures, the physical component summary (PCS) and the mental component summary (MCS) were also analyzed.
Metabolic syndrome (MS)
According to the NCEP ATP III criteria [23], a race-specific waist circumference threshold was applied to prevent a discrepancy in MS prevalence. The cut-off values for normal waist circumference in men and women were 90 cm and 80 cm, respectively, for Asian people. In this study, the ATP III criteria define MS as the presence of at least three of the following five traits: 1) abdominal obesity, defined as a waist circumference in men and women of ≥90 cm (35 inches) and ≥80 cm (31.5 inches), respectively; 2) serum triglycerides ≥150 mg/dL (1.7 mmol/L) or drug treatment for elevated triglycerides; 3) serum HDL cholesterol <40 mg/dL (1 mmol/L) in men and <50 mg/dL (1.3 mmol/L) in women or drug treatment for low HDL-C; 4) blood pressure ≥130/85 mmHg or drug treatment for elevated blood pressure; or 5) fasting plasma glucose (FPG) ≥100 mg/dL (5.6 mmol/L) or drug treatment for elevated blood glucose.
Serum insulin and fasting blood sugar were used for the analysis of IR (HOMA-IR) in this study. The analysis of HOMA-IR for IR was not suitable for patients with DM or those that took medicine for blood sugar control [28–29, 32]. Although patients undergoing drug treatment for elevated blood sugar were classified as having MS by the NICE ATPIII criteria, patients treated by oral hypoglycemia agents or insulin injections were excluded from our analysis.
Statistical analysis
Values are expressed as means and standard deviations (SD) for continuous data. Categorical data were analyzed with the Chi-square test or Fisher’s exact test, as appropriate. The Cochran–Mantel–Haenszel (CMH) statistic was used to test the conditional independence of data in 2×2×2 tables. All statistical tests were 2-tailed. A p- value of <0.05 was considered statistically significant. The association between metabolic parameters and H. pylori serostatus was evaluated by the Pearson correlation coefficient and multivariate logistic regression analysis after adjusting for sex as a potential confounder. Statistical analyses were performed using the statistical package SPSS for windows (Version 14.0, Chicago, IL, USA).
Results
A total of 829subjects (560 women) were initially enrolled. Eighteen subjects were excluded because of a past history of H. pylori eradication therapy. These 18 subjeccts were all more than 50 years old and had IgG anti H. pylori. Then 811 subjects were finally included for this study. The mean age was 59.2 years. The demographic data are listed in Table 1. Serum antibodies for H. pylori (IgG anti H. pylori) were positive in 62.8% (509/811) of subjects. According to the ATP III criteria, MS was present in 36.6% (297/811) subjects. The percents of subjects exhibited HOMA-IR indexs greater than 2, 2.5 or 3 were 34.0% (276/811), 25.5% (207/811) and 18.9% (153/811) respectively. Subjects were divided into two groups according to H. pylori antibody serostatus. The demographic data are shown in Table 2. The positivity ratio of the H. pylori antibody was approximately 60% in every age stratum and did not change significantly with increasing age.
When compared with subjects without the H. pylori antibody, subjects with the H. pylori antibody had higher rates of hypertension, HOMR-IR (including index >2, >2.5 or >3), and higher diastolic/ systolic blood pressure, cholesterol and TNF-α. However, there was no significant difference in the mean serum adiponectin, leptin and HS-CRP values between these two groups.
A receiver operating characteristics (ROC) curve was applied to establish the optimal age cut-off point to differentiate the MS distribution between subjects with or without H. pylori antibodies. The optimal cut-off point was computed by maximization of Youden’s index (sensitivity+specificity-1) in the ROC curve analysis. Table 3 shows the sensitivity, specificity and Youden’s index. We found that Youden’s index was maximal (0.034) at age 50. Hence, the cut-off point was set to 50 y/o to differentiate the MS distribution between subjects with or without H. pylori antibody.
The H. pylori infection rate, frequency of MS and HOMA-IR stratified by age are shown in Table 4 and Table 5. Among subjects less than 50 y/o (Table 4), there were significant differences in the rates of H. pylori antibody seropositivity and HOMA-IR indexs between subjects with MS and those without MS (H. pylori antibody rate 76.7% vs. 53.7%, p = 0.007; HOMA-IR >2 rate, 67.4% vs. 15.4%, >2.5 rate, 60.5% vs. 9.6%, >3 rate, 46.5% vs. 5.1%, all p<0.001). In Table 5, the MS rates were significantly different between subjects with the H. pylori antibody and those without the H. pylori antibody in different age groups (p-value < 0.001).
The H. pylori antibody was correlated with MS in subjects < 50 y/o (r2 = 0.201, p = 0.007), which is shown in Table 6. Our hypothesis suggested that H. pylori infection induces the expression of inflammatory cytokines (TNF-α), which results in IR and MS. Although the factor TNF-α was correlated with H. pylori infection in the > 50 y/o group, this finding could not support our hypothesis because there was no statistical correlation between the H. pylori antibody status and MS in this group. Further investigations are required to determine whether other inflammatory cytokines or adipokines can induce IR and MS.
A logistic regression analysis including the covariates leptin, adiponectin, TNF-α, AST, ALT, HS-CRP, HOMA-IR (>2, 2.5 or 3) and H. pylori antibody serostatus was performed. The associations with predictors and the presence of MS are listed in Table 7. A HOMA-IR index >2.5, H. pylori antibodies and leptin were found to be predictors of MS in subjects less than 50 y/o. The estimated odds of MS for a subject with the H. pylori antibody was 3.717 (95% CI = 1.086–12.719) times that of a subject without the H. pylori antibody. In addition, no difference in H. pylori antibody status was detected for MS prediction in subjects more than 50 y/o (p = 0.462). When we applied the different HOMA-IR cut-off values (2 or 3), the result of H. pylori antibody as a predictor for MS was the same as using the HOMA-IR cut-off value of 2.5.There were no significant differences for educational districts and occupational status between subjects with H. pylori antibodies and those without antibodies in this study.
Among the SF-36 domain, subjects with MS had lower scores than those without MS only in the sections of physical function (79.7 ± 24.1 vs. 86.4 ± 19.3, p = 0.000), general health perceptions (57.3±17.8 vs. 60.2±17.8, p = 0.033) and physical component summary (51.6 ± 7.8 vs. 53.5 ± 6.6, p = 0.001). There was no statistical difference in the scores of other sections, including vitality, bodily pain, physical role functioning, emotional role functioning, social role functioning, mental health and mental component summary, between the subjects with MS and those without MS. However, there was no statistical difference of the score among any SF-36 section between subjects with and without anti H. pylori IgG sero-positivity.
Discussion
According to a systemic review, there is a potential association between H. pylori infection and IR [20]. Although the mechanism that links H. pylori infection and IR remains unclear, a chronic inflammatory response and the associated cytokine release following H. pylori infection may be responsible for IR pathogenesis [18–20]. The prevalence of both H. pylori infection and MS were higher in aged patients [33, 34]. A coincidence of H. pylori infection and MS has been reported by some studies [33,35,36], but conflicting results supporting a role of H. pylori in promoting MS and IR have been reported by other studies [15,18–20,37,38]. According to Gunji et al., in two large Japanese population studies, H. pylori infection was significantly associated with IR and MS regardless of subject age. However, the mean age of enrolled subjects in their study was 47.3 y/o, which was younger than the mean age of our enrolled subjects (59.2 y/o). The current study revealed that age classification may be important for the analysis of relationships between H. pylori infection and IR/MS. Among subjects aged < 50 y/o, subjects with an H. pylori infection may have a higher likelihood of acquiring IR and MS than those without H. pylori infection. People with the H. pylori antibody have a nearly 3.7 times higher likelihood of having MS than those without the H. pylori antibody in this study. However, among subjects aged > 50 y/o, the rate of MS distribution was not significantly different regardless of H. pylori infection. This may be due to the presence of more risk factors for the development of MS in people > 50 y/o, such as hyperlipidemia, hyperglycemia or hypertension. Other factors, such as systemic or local inflammations and being overweight may affect H. pylori inflammation and MS development.
Because most patients acquire H. pylori infections during childhood, the inflammatory influences of H. pylori infection on MS and IR might begin or show prominence at a young age. Most adult patients who got H pylori infection at childhood are asymptomatic. There was no statistical difference in the scores among any SF-36 section between subjects with and without anti H pylori IgG sero-positivity in the current study. This finding may imply H pylori infection dose not influence quality of life in the most of our subjects. In this study, the seropositive rate of the H. pylori antibody was consistently approximately 60% in all age classifications (30 to 80 y/o), which indicates that most enrolled patients acquire H. pylori infections before 30 years of age. Data collection from adolescents or young adults is necessary for future studies to elucidate the role of current H. pylori infections in MS development. Because the accuracy of serology test for H pylori antibody may be lower in elderly subjects [39], elderly subjects with detected serum H. pylori antibodies may have no current H. pylori infection. This condition might partially explain the observation in our study, which showed H. pylori infection (by serology test) could not be a predictor for MS in aged subjects more than 50 y/o.
Previous studies have shown that the presence of H. pylori antibodies is associated with an altered serum lipid profile and is considered a risk factor for atherosclerosis [40,41]. It is well known that TG levels rise and HDL cholesterol levels decline post H. pylori infection [40–42]. The interaction between H. pylori and lipid levels may be mediated by adipokines, such as adiponectin and leptin, or inflammatory cytokines, such as HS-CRP or TNF-α [4–11]. These cytokines affect metabolic risk factors, including blood pressure, lipid profile, glucose intolerance, atherosclerosis and cardiovascular diseases [10–14]. In the current study, factors such as adiponectin, leptin, HS-CRP or TNF-α were highly associated with MS in the correlation and regression analysis, which is compatible with previous studies [4–11]. Higher serum mean TG, VLDL, and cholesterol values and increased blood pressure were observed in the subjects with H. pylori antibodies compared to those without H pylori antibodies.
When multivariate logistic regression analysis was applied, with factors including adiponectin, leptin, TNF-α, HS-CRP, AST, ALT, HOMA-IR index and H. pylori antibody status, H. pylori antibody status was found to be a predictor for MS in subjects aged < 50 y/o. A possible reason for the correlation between H. pylori antibody status and MS was IR. The factor of HOMA-IR was also correlated with H. pylori antibody status in this study. However, there was no significant difference in the mean serum values of adiponectin, leptin and HS-CRP between subjects with H. pylori antibodies and those without H. pylori antibodies. Only the TNF-α mean value was higher in subjects with H. pylori antibodies than those without antibodies. Other cytokines or adipokines in addition to adiponectin, leptin, TNF-α or HS-CRP may be involved in the interaction between IR and H. pylori infection. Hence, other cytokines or adipokines, such as interleukin 6 or 8, ghrelin or resistin may be utilized to elucidate the pathogenic mechanisms of MS and H. pylori infection in the future.
Some limitations were present in this study. First, H. pylori infection status was evaluated solely with an H. pylori-specific IgG antibody without other confirmed assessments such as a urease breath test or a rapid urease test. The presence of the H. pylori antibody does not completely correspond to current H. pylori infection [37]. However, the serostatus of the H. pylori antibody maybe accurate for determining current H. pylori infection in young patients. Because most patients acquire H. pylori infection during childhood and maintain chronic infection status for a long time, the serostatus of H. pylori antibody may remain constant in young patients if they do not receive H pylori eradication therapy. Moreover, the serology test for the H. pylori antibody is a highly sensitive and cheap mass screening method that can be used in areas with a high prevalence H. pylori infection, such as the areas examined in the present study.
The second limitation was selection bias. Our study originated from community-based health checkup data. The participants may consist of older adults with underlying diseases and a desire for medical examinations. There was only 179 subjects aged less than 50 years old included in this study. As with the other cross-sectional study designs, unmeasured confounding factors or covariates might exist in this study.
In conclusion, subjects with H. pylori antibodies had a higher prevalence of IR (HOMA-IR >2), hypertension, and increased TNF-α than those without H pylori antibodies. For subjects < 50 y/o, seropositive status for the H. pylori antibody was a predictor for MS. The estimated odds of MS in a subject with H. pylori antibodies was 3.717 (95% CI = 1.086–12.719) times higher than that of a subject without H. pylori antibodies when a cut-off value of 2.5 for HOMA-IR index. However, further study is required to determine if a causal relationship exists between H. pylori and MS.
Acknowledgments
We acknowledge Dr. Kuan-Fu Chen for help in collecting serum samples from the core unit of the community medicine research center.
Author Contributions
Conceived and designed the experiments: LWC. Performed the experiments: LWC CYC KJY. Analyzed the data: LWC KJY CYC. Contributed reagents/materials/analysis tools: CYC RNC SFK CHC. Wrote the paper: LWC RNC.
References
- 1. Crabtree JE (1996) Gastric mucosal inflammatory responses to Helicobacter pylori. Aliment Pharmacol Ther 10 (Suppl 1): 29–37. pmid:8730257
- 2. Ernst PB, Jin Y, Reyes VE, Crowe SE (1994) The role of the local immune response in the pathogenesis of peptic ulcer formation. Scand J Gastroenterol 205 (Suppl 1): 22–28.
- 3. Kusters JG, van Vliet AH, Kuipers EJ (2006) Pathogenesis of Helicobacter pylori infection. Clin Microbiol Rev 19: 449–490. pmid:16847081
- 4. Moss SF, Legon S, Davies J, Calam J (1994) Cytokine gene expression in Helicobacter pylori associated antral gastritis. Gut 35: 1567–1570. pmid:7828974
- 5. Thalmaier U, Lehn N, Pfeffer K, Stolte M, Vieth M, Schneider-Brachert W (2002) Role of tumor necrosis factor alpha in Helicobacter pylori gastritis in tumor necrosis factor receptor 1-deficient mice. Infect Immun 70: 3149–3155. pmid:12011009
- 6. Noach LA, Bosma NB, Jansen J, Hoek FJ, van Deventer SJ, Tytgat GN (1994) Mucosal tumor necrosis factor-alpha, interleukin-1 beta, and interleukin-8 production in patients with Helicobacter pylori infection. Scand J Gastroenterol 29: 425–429. pmid:8036458
- 7. Breidert M, Miehlke S, Glasow A, Orban Z, Stolte M, Ehninger G, et al (1999) Leptin and its receptor in normal human gastric mucosa and in Helicobacter pylori-associated gastritis. Scand J Gastroenterol 34: 954–961. pmid:10563663
- 8. Azuma T, Suto H, Ito Y, Ohtani M, Dojo M, Kuriyama M, et al (2001) Gastric leptin and Helicobacter pylori infection. Gut 49: 324–329. pmid:11511551
- 9. Roper J, Francois F, Shue PL, Mourad MS, Pei Z, Olivares de Perez AZ, et al (2008) Leptin and ghrelin in relation to Helicobacter pylori status in adult males. J Clin Endocrinol Metab 93: 2350–2357. pmid:18397989
- 10. Hotamisligil GS, Shargill NS, Spiegelman BM (1993) Adipose expression of tumor necrosis factor-alpha: direct role in obesity-linked insulin resistance. Science 259: 87–91. pmid:7678183
- 11. Cohen B, Novick D, Rubinstein M (1996) Modulation of insulin activities by leptin. Science 274: 1185–1188. pmid:8895466
- 12. Matthaei S, Stumvoll M, Kellerer M, Häring HU (2000) Pathophysiology and pharmacological treatment of insulin resistance. Endocr Rev 21: 585–618. pmid:11133066
- 13. Shoelson SE, Herrero L, Naaz A (2007) Obesity, inflammation, and insulin resistance. Gastroenterol 132: 2169–2180. pmid:17498510
- 14. Ferrannini E, Haffner SM, Mitchell BD, Stern MP (1991) Hyperinsulinaemia: the key feature of a cardiovascular and metabolic syndrome. Diabetologia 34: 416–422. pmid:1884900
- 15. Aydemir S, Bayraktaroglu T, Sert M, Sokmen C, Atmaca H, Mungan G, et al (2005) The effect of Helicobacter pylori on insulin resistance. Dig Dis Sci 50: 2090–2093. pmid:16240220
- 16. Aslan M, Horoz M, Nazligul Y, Bolukbas C, Bolukbas FF, Selek S, et al (2006) Insulin resistance in H pylori infection and its association with oxidative stress. World J Gastroenterol 12: 6865–6868. pmid:17106938
- 17. Candelli M, Rigante D, Marietti G, Nista EC, Crea F, Bartolozzi F, et al (2003) Helicobacter pylori, gastrointestinal symptoms, and metabolic control in young type 1 diabetes mellitus patients. Pediatr 111: 800–803.
- 18. Gunji T, Matsuhashi N, Sato H, Fujibayashi K, Okumura M, Sasabe N, et al (2008) Helicobacter pylori infection is significantly associated with metabolic syndrome in the Japanese population. Am J Gastroenterol 103: 3005–3010. pmid:19086952
- 19. Gunji T, Matsuhashi N, Sato H, Fujibayashi K, Okumura M, Sasabe N, et al (2009) Helicobacter pylori infection significantly increases insulin resistance in the asymptomatic Japanese population. Helicobacter 14: 144–150. pmid:19751440
- 20. Polyzos SA, Kountouras J, Zavos C, Deretzi G (2011) The association between Helicobacter pylori infection and insulin resistance: A systematic review. Helicobacter 16: 79–88. pmid:21435084
- 21. Albaker WI (2011) Helicobacter pylori infection and its relationship to metabolic syndrome: is it a myth or fact? Saudi J Gastroenterol 17: 165–169. pmid:21546717
- 22. Naja F, Nasreddine L, Hwalla N, Moghames P, Shoaib H, Fatfat M, et al (2012) Association of H. pylori infection with insulin resistance and metabolic syndrome among Lebanese adults. Helicobacter 17: 444–451. pmid:23066847
- 23. Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (2001) Executive summary of the Third Report of the National Cholesterol Education Program (NCEP) expert panel on detection, evaluation, and treatment of high blood cholesterol in adults (Adult Treatment Panel III). JAMA 285: 2486–2497. pmid:11368702
- 24. Grundy SM, Cleeman JI, Daniels SR, Donato KA, Eckel RH, Franklin BA, et al (2005) Diagnosis and management of the metabolic syndrome: an American Heart Association/National Heart, Lung, and Blood Institute scientific statement. Circulation 112: 2735–2752. pmid:16157765
- 25. Alberti KGMM, Zimmet P, Shaw J (2006) Metabolic syndrome—a new world-wide definition.A consensus statement from the international diabetes federation. Diabet Med 23: 469–480. pmid:16681555
- 26. Alberti KGMM, Zimmet P, Shaw J, IDF Epidemiology Task Force Consensus Group (2005) The metabolic syndrome—a new worldwide definition. Lancet 366: 1059–1062. pmid:16182882
- 27. Saad MAN, Cardoso GP, Martins WdeA, Velarde LG, da Cruz Filho RA (2014) Prevalence of metabolic syndrome in elderly and agreement among four diagnostic criteria. Arq Bras Cardiol 102: 263–269. pmid:24676226
- 28. Matthews DR, Hosker JP, Rudenski AS, Naylor BA, Treacher DF, Turner RC (1985) Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia 28: 412–419. pmid:3899825
- 29. Gayoso-Diz P, Otero-González A, Rodriguez-Alvarez MX, Gude F, García F, García F, et al (2013) Insulin resistance (HOMA-IR) cut-off values and the metabolic syndrome in a general adult population: effect of gender and age: EPIRCE cross-sectional study. BMC Endocr Disord 13: 47–57. pmid:24131857
- 30. Ware JE, Sherburne CD (1992) The MOS 36-item short-form healthy survey (SF-36). Med Care 30:473–483. pmid:1593914
- 31. Tseng HM, Lu JR, Gandek B (2003) Cultural issues in using the SF-36 health survey in Asia: results from Taiwan. Health Qual Life Outcomes 1:72–81 pmid:14641915
- 32. Tresaco B, Bueno G, Pineda I, Moreno LA, Garagorri JM, Bueno M (2005) Homeostatic model assessment (HOMA) index cut-off values to identify the metabolic syndrome in children. J Physiol Biochem 61: 381–388. pmid:16180336
- 33. Gillum RF (2004) Infection with Helicobacter pylori, coronary heart disease, cardiovascular risk factors, and systemic inflammation: the third national health and nutrition examination survey. J Natl Med Assoc 96: 1470–1476. pmid:15586651
- 34. Woodward M, Morrison C, McColl K (2000) An investigation into factors associated with Helicobacter pylori infection. J Clin Epidemiol 53: 175–181. pmid:10729690
- 35. Cammarota G, Pasceri V, Gasbarrini A, Gasbarrini G (2000) Helicobacter pylori is an aetiological factor for ischaemic heart disease: the case against. Dig Liver Dis 32: 65–68. pmid:10975758
- 36. Andraws R, Berger JS, Brown DL (2005) Effects of antibiotic therapy on outcomes of patients with coronary artery disease: a meta-analysis of randomized controlled trials. JAMA 293: 2641–2647. pmid:15928286
- 37. Danesh J, Peto R (1998) Risk factors for coronary heart disease and infection with Helicobacter pylori: meta-analysis of 18 studies. BMJ 316: 1130–1132. pmid:9552950
- 38. Sung KC, Rhee EJ, Ryu SH, Beck SH (2005) Prevalence of Helicobacter pylori infection and its association with cardiovascular risk factors in Korean adults. Int J Cardiol 102: 411–417. pmid:16004885
- 39. Liston R, Pitt MA, Banerjee AK (1996) IgG ELISA antibodies and detection of Helicobacter pylori in elderly patients. Lancet. 347:269. pmid:8551920
- 40. Kinjo K, Sato H, Sato H, Shiotani I, Kurotobi T, Ohnishi Y, et al (2002) Prevalence of Helicobacter pylori infection and its link to coronary risk factors in Japanese patients with acute myocardial infarction. Circ J 66: 805–810. pmid:12224816
- 41. Kanbay M, Gür G, Yücel M, Yilmaz U, Boyacioğlu S (2005) Does eradication of Helicobacter pylori infection help normalize serum lipid and CRP levels? Dig Dis Sci 50: 1228–1231. pmid:16047464
- 42. Chimienti G, Russo F, Lamanuzzi BL, Nardulli M, Messa C, Di Leo A, et al (2003) Helicobacter pylori is associated with modified lipid profile: impact on lipoprotein(a). Clin Biochem 36: 359–365. pmid:12849867