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Article

A Significant Association between Type 1 Diabetes and Helicobacter pylori Infection: A Meta-Analysis Study

by
Wei-Kian Chua
1,
Yi-Kai Hong
2,3,4,
Shu-Wei Hu
5,6,7,
Hueng-Chuen Fan
7,8,9,* and
Wei-Hsin Ting
10,11,*
1
Division of Pediatric Endocrinology, Department of Pediatrics, Tungs’ Taichung MetroHarbor Hospital, Taichung 43503, Taiwan
2
Department of Dermatology, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan 70101, Taiwan
3
International Center for Wound Repair and Regeneration (iWRR), National Cheng Kung University, Tainan 70101, Taiwan
4
Department of Dermatology, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
5
Division of Pediatric Gastroenterology, Department of Pediatrics, Tungs’ Taichung MetroHarbor Hospital, Taichung 43503, Taiwan
6
Ph.D. Program in Translational Medicine, National Chung Hsing University, Taichung 40227, Taiwan
7
Rong Hsing Research Center for Translational Medicine, National Chung Hsing University, Taichung 40227, Taiwan
8
Division of Pediatric Neurology, Department of Pediatrics, Tungs’ Taichung MetroHarbor Hospital, Taichung 43503, Taiwan
9
Department of Rehabilitation, Jenteh Junior College of Medicine, Nursing and Management, Miaoli 35664, Taiwan
10
Department of Pediatric Endocrinology, MacKay Children’s Hospital, Taipei 10449, Taiwan
11
Department of Medicine, MacKay Medical College, New Taipei 25245, Taiwan
 
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Authors to whom correspondence should be addressed.
Medicina 2024, 60(1), 119; https://doi.org/10.3390/medicina60010119
Submission received: 17 November 2023 / Revised: 11 December 2023 / Accepted: 28 December 2023 / Published: 9 January 2024
(This article belongs to the Section Pediatrics)
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Abstract

:
Background and Objectives: Type 1 diabetes mellitus (T1DM) is a chronic and serious condition that is characterized by inadequate pancreatic-β-cells’ insulin production. The connection between T1DM and Helicobacter pylori infection remains uncertain. This study aimed to conduct a systematic meta-analysis to examine the association between H. pylori infection, hemoglobin A1c levels, and the development of T1DM. Materials and Methods: The initial search identified 451 articles on the association between H. pylori infection and T1DM. Among them, 12 articles had 2797 participants who met the inclusion criteria for an advanced meta-analysis. Results: A significant association was observed between H. pylori infection and T1DM (OR 1.77, 95% CI 1.47–2.12, p < 0.0001), with heterogeneity: Tau2 = 0.47; Chi2 = 57.07, df = 11 (p < 0.0001); I2 = 81%. Subgroup analysis showed that H. pylori infection was significantly associated with a longer duration of T1DM and higher hemoglobin A1c levels (p < 0.001 for both) but not with age at T1DM diagnosis (p = 0.306). Conclusions: These findings contribute to the understanding of the association between H. pylori infection and T1DM and highlight the potential role of H. pylori in influencing the duration and glycemic control of diabetes. Therefore, pediatric patients who have longstanding T1DM and poor glycemic control should be screened for H. pylori infection.

1. Introduction

Type 1 diabetes mellitus (T1DM) is a chronic and notably severe medical condition that is recognized for its defining feature of an inadequate production of insulin by the pancreatic β-cells. Typically, this condition has been conventionally associated with its predominant occurrence in the pediatric and young adult demographic. Nonetheless, it is imperative to note that T1DM can potentially manifest across a broad spectrum of ages, dispelling the notion that it is solely confined to the younger population [1]. Notably, a substantial majority (85% to 90%) of individuals with T1DM have autoantibodies that specifically target key proteins, including insulin, glutamic acid decarboxylase 65, insulinoma-associated autoantigen 2, zinc transporter 8, and tyrosine phosphatase IA-2β. This underscores the complex interplay of immune responses and genetic predisposition, which plays a pivotal role in the pathogenesis of T1DM [2,3]. Autoimmune destruction of β cells is the critical precursor of the potential onset of T1DM. Therefore, immediate and precise diagnosis is important to manage this condition effectively. Timely diagnosis not only facilitates the implementation of appropriate medical interventions but can also prevent the complications of T1DM. By recognizing and addressing the condition at an early stage, healthcare practitioners can significantly enhance the overall quality of life of individuals with T1DM.
Helicobacter pylori is a prevalent Gram-negative bacterium that has a notable pathogenic profile and can spread widely to a substantial percentage (i.e., >50%) of the worldwide population. H. pylori infection has a substantial ubiquity in developing nations, with prevalence rates of approximately 85% to 95%. In contrast, in developed countries, this prevalence assumes a range of 30% to 50%, underscoring a significant disparity influenced by socioeconomic and environmental factors [4,5]. An intriguing facet of this epidemiological landscape is the noteworthy downward trajectory observed in the prevalence of H. pylori infection across European countries since the dawn of the twenty-first century. This trend hints at evolving factors such as changes in lifestyle, improved hygiene practices, and advances in healthcare that have contributed to a decline in the incidence of this infection within these geographical areas. Conversely, Asian countries exhibit a relatively stable prevalence of H. pylori infection over the same time frame, suggesting that the factors that influence the persistence of this infection vary across different regions. The intricate interplay between genetics, cultural practices, dietary habits, and healthcare infrastructure potentially contributes to this stability in the prevalence of H. pylori in Asian populations [5,6]. H. pylori infection exerts a wide-ranging influence on human health, exerting its effects not only on gastric systems but also on various extra-gastric systems. H. pylori infection has a spectrum of complications that extend beyond the stomach and carry consequences that encompass both well-established gastric issues and an array of less commonly recognized extra-gastric disorders. For gastric complications, H. pylori infection orchestrates a cascade of pathological events that encompass gastritis, peptic ulcer disease, functional dyspepsia, gastroesophageal reflux disease, and the formidable specter of gastric cancer. These interlinked conditions collectively constitute a spectrum of disturbances that highlight the intricate interplay between H. pylori and the gastric environment. However, the impact of H. pylori extends far beyond the stomach and is intricately connected with several extra-gastric complications. The repercussions of H. pylori infection transcend the anatomical confines of the stomach and may include cardiopulmonary diseases, such as coronary artery disease and asthma; hematologic disorders, including iron deficiency anemia and immune thrombocytopenic purpura; and neurologic maladies like ischemic stroke, Parkinson’s disease, Alzheimer’s disease, Guillain–Barré syndrome, and migraines. Moreover, the influence of H. pylori delves into dermatologic ailments, exemplified by its link to chronic spontaneous urticaria, as well as metabolic disorders that encompass metabolic syndrome and insulin resistance. Evidently, the diverse and intricate effects of H. pylori infection underscore its pivotal role in human health and emphasize its capability to affect multiple bodily systems. This intricate interplay and the potential to manifest in multifaceted ways further exemplify the need for a comprehensive understanding and management of H. pylori infection [7,8,9,10].
Numerous comprehensive studies have consistently demonstrated a robust and noteworthy correlation between the presence of H. pylori infection, a bacterial infection primarily affecting the stomach lining, and the notable elevation of the level of hemoglobin A1c (HbA1c) [11,12,13,14], which is a pivotal biomarker of long-term blood sugar control and reflects the average blood sugar level over a span of several months. This correlation had been particularly pronounced in a subset of individuals with type 2 diabetes mellitus (T2DM), which is a metabolic disorder that is characterized by high blood sugar levels secondary to insulin resistance. The intriguing findings of these previous studies indicated that H. pylori infection might exert a tangible influence on glycemic control, as evidenced by the increased HbA1c levels. Moreover, previous studies that were conducted across diverse geographical regions and populations have consistently shown a clear trend of a greater likelihood of H. pylori infection in individuals with T1DM than in their nondiabetic counterparts. This observation led to the necessity of elucidating the intricate interplay between H. pylori and the autoimmune processes that underlie the development of T1DM. The increased serological prevalence rate of H. pylori infection in patients with T1DM compels the need to investigate the potentially shared mechanisms or immunological conditions between these seemingly disparate conditions. Scientists have meticulously studied the possible immunomodulatory effects of H. pylori infection in the context of T1DM and sought to ascertain the contribution of this infection to the complex autoimmune cascade that leads to β cell destruction [15]. Hence, in light of the existing knowledge gaps and the imperative to comprehensively grasp the intricate relationships at play, the primary objective of the present research endeavor was to meticulously undertake a systematic meta-analysis. This endeavor, undertaken with methodological rigor and precision, sought to discern and quantify the overarching effect size that characterizes the intricate interplay among several pivotal factors, including H. pylori infection, HbA1c levels, and the eventual onset of T1DM in pediatric patients.
Numerous studies have shown a positive association between H. pylori infection and diabetes [16] and that, among the most common chronic diseases in children and adolescents, H. pylori infection was a potential risk factor for diabetes and T1DM [17,18]. However, we recognize the lack of pediatric data and aimed to conduct this meta-analysis to determine the association of H. pylori infection with HbA1c levels and the development of T1DM in pediatric patients.

2. Materials and Methods

2.1. Data Collection

This meta-analysis was performed and reported in compliance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) Statement [19,20]. All original articles were searched for on international databases, including NCBI (PubMed), ISI Web of Science, EMBASE, and Cochrane Library, without language limitations. The search strategy was conducted using the PICOS tool, which uses data on population (children), intervention (diabetes), outcomes (H. pylori infection), and study type (case–control study). The complete list of searched keywords was Diabetes, Diabetes Mellitus (type 1), Insulin Dependent, IDDM, Insulin Sensitivity, Helicobacter pylori, campylobacter pylori, H Pylori, Child, Children, Young patients, Pediatric, and Adolescents. The search was performed using the Medical Subject Headings and free keywords. The keywords selected for the search were (Children or Child or Young patients or Pediatric or Adolescents) and [Diabetes or T1DM or Diabetes Mellitus (type 1) or Insulin Dependent or IDDM or Insulin Sensitivity] and (Helicobacter pylori or Campylobacter pylori or H. pylori).
The studies were identified independently by two investigators, and disagreements were resolved by consensus. In the case of duplicate studies, only the most recent and informative publications were included in the analysis. Articles meeting the following inclusion criteria were evaluated: (1) case–control studies, (2) those with patients aged <20 years, (3) those that used H. pylori as an exposure variable. Case reports, reviews, meta-analyses, cross-sectional studies, and cohort studies were excluded from the analysis. Two investigators independently extracted the following data from eligible studies: year, nation, study design, sample size, proportion of sex, age, control group, odds ratio, type of diabetes, test method for H. pylori, and the control variable.

2.2. Statistical Analysis

The meta-analysis was performed in accordance with the PRISMA guidelines [19]. Odds ratios (ORs) and standard errors were used to describe the results. When required, the OR with 95% confidence interval (CI) was calculated using MedCalc (https://www.medcalc.org/calc/odds_ratio.php/) (Version 22.017; accessed on 14 October 2023). Differences in the mean and standard deviation values were used for subgroup analysis. The random-effect model was used to combine the estimated effects [21]. Statistical heterogeneity was assessed using the I2 test, with I2 representing the proportion of the total outcome variability that was attributable to the variability among the studies [22].
All statistical analyses were performed using the Comprehensive Meta-Analysis (CMA) software 4.0 (Biostat Inc., Englewood, NJ, USA), and a p-value of <0.05 was considered statistically significant.

3. Results

3.1. Characteristics and Methodologies of the Included Studies

The PRISMA flowchart (Figure 1) shows the study selection and inclusion process. The initial phase of the research endeavor encompassed a comprehensive search that yielded a substantial corpus of 451 articles exploring a potential association between H. pylori infection and T1DM. We excluded 439 articles using a systematic filtering process. This exclusion covered a range of factors, including 106 duplicate articles, 267 pieces with outcomes not directly pertinent to the investigation, as well as 66 articles categorized as reviews, letters, meta-analysis studies, and case reports. Following this rigorous culling, a meticulously curated set of 12 articles were selected and emerged as prime candidates for the study, as illustrated in Figure 1 [23,24,25,26,27,28,29,30,31,32,33,34].
Notably, the diversity of this pool was marked by one study, which included pediatric participants without specific age details; the remaining studies included patients aged 10–20 years. A comprehensive delineation of the salient features of these chosen studies is provided in Table 1. Overall, this advanced meta-analysis synthesized data from a noteworthy cohort of 2797 participants with T1DM. Delving deeper, the distribution between cases and controls came to 1159 and 1638, respectively, encapsulating a substantial breadth of relevant data for a comprehensive investigation into the potential relationship between H. pylori infection and T1DM. In six studies, H. pylori infection was diagnosed using the enzyme-linked immunosorbent assay. The remaining studies used other methods, such as the 13C urea breath test, RIBASIA, rapid urease test, enzyme immunoassay (EIA), and stool antigen test. To ensure the integrity of the findings and to ascertain the potential impact of publication bias, a methodical assessment was undertaken. This endeavor involved the construction of a funnel plot, a graphical representation that capitalizes on the logarithm and logarithm standard error of the odds ratio (OR) values attributed to H. pylori infection. The primary purpose of this construction was to visualize the distribution of studies in relation to their precision and effect size. Upon meticulous examination of the funnel plot, a distinct symmetrical pattern emerged, indicating a seemingly uniform spread of studies across the range of effect sizes. This observation, while suggestive, necessitated a more quantitative and robust analysis to corroborate the absence of publication bias. In this pursuit, the Begg’s rank correlation method was harnessed, which is a statistical tool designed to probe for potential correlations between study size and effect size. The outcomes of this analytical venture showcased a statistically non-significant result (Pr > |z| = 0.656 > 0.05), thereby indicating that the distribution and effect size of the studies were not influenced by publication bias. This result conferred a high degree of confidence in the impartiality and credibility of the research landscape and effectively ruled out systematic distortion of the analyzed data (Figure 2).

3.2. Meta-Analysis Results

An in-depth analysis of the quantitative breakdown showed that the prevalence of H. pylori infection was higher in the diabetes cohort (45.87%, n = 561) than in healthy individuals (24.27%, n = 413). This result highlighted a marked discrepancy in the prevalence of H. pylori infection between the two cohorts. Moreover, H. pylori infection was significantly associated with T1DM (OR 1.77, 95% CI 1.47–2.12, p < 0.0001), with heterogeneity: Tau2 = 0.47; Chi2 = 57.07, df = 11 (p < 0.0001); I2 = 81% (Figure 3).
Data, including age at diagnosis of T1DM, HbA1c levels, and duration of diabetes, were comprehensively collected from patients with diabetes for an advanced subgroup analysis. The participants within this study were thoughtfully categorized into distinct groups: the H. pylori-positive (HP+) group and the H. pylori-negative (HP−) group. This discerning division of participants enabled a focused and granular analysis, allowing for the disentangling of the complex interplay between H. pylori infection and the specific subsets characterized by distinct variables such as age at diagnosis, HbA1c levels, and duration of diabetes. By delving into this dichotomy of HP+ and HP− groups, the research team endeavored to unveil the association between H. pylori infection and these respective subgroups (Table 2).
Interestingly, this meticulous analysis found a nonsignificant association (p = 0.306) between H. pylori infection and age at T1DM diagnosis in this pediatric population. This absence of a significant association implied an inherent complexity in the relationship between H. pylori infection and T1DM and encouraged a deeper exploration of the factors that contributed to this result (heterogeneity: Chi2 = 18.21, df = 6 (p = 0.006); I2 = 67%) (Supplementary Figure S1). On the other hand, H. pylori infection was significantly associated with a prolonged duration of diabetes (p < 0.001; heterogeneity: Tau2 = 22.97; Chi2 = 554.16, df = 6, p < 0.00001; I2 = 99%) (Figure 4) and high HbA1c levels (p < 0.001; heterogeneity: Tau2 = 0.63; Chi2 = 105.34, df = 5, p < 0.00001; I2 = 95%) (Figure 5). The multifaceted relationships of H. pylori infection with age at T1DM diagnosis, diabetes duration, and HbA1c levels suggested that presence of and the need to further explore the intricate interactions and underlying mechanisms.

3.3. Sensitivity Analysis Results

Sensitivity analysis was performed using the statistical software Comprehensive Meta-Analysis (CMA) 4.0. Among the seven studies included, the OR was 2.30 (95% CI 1.79–2.96, p < 0.001; heterogeneity: Chi2 = 14.61, df = 6, p = 0.11; I2 = 40%) (Supplementary Figure S2A). The difference in the mean age had an OR of 0.13 (95% CI −0.12 to 0.38; heterogeneity: Tau2 = 0.19; Chi2 = 6.21, df = 4, p = 0.18; I2 = 36%) (Supplementary Figure S2B). The difference in the mean duration of diabetes had an OR of 0.70 (95% CI 0.52–0.87; heterogeneity: Tau2 = 0.07; Chi2 = 7.74, df = 6, p = 0.10; I2 = 48%) (Supplementary Figure S2C). The difference in the mean HbA1c level had an OR of 0.42 (95% CI 0.29–0.54; heterogeneity: Chi2 = 22.10, df = 5, p = 0.0002; I2 = 82%) (Supplementary Figure S2D).

4. Discussion

In this meta-analysis, H. pylori infection was found to have a positive association with elevated HbA1c levels and duration of T1DM in pediatric patients. These results were in accordance with those of previous worldwide studies. The seroprevalence of H. pylori was reported to be significantly higher in patients with T1DM than in healthy control individuals [29,30]. In one study on patients with diabetes, the prevalence of H. pylori infection was relatively high in those who were aged >12 years and had relatively long disease duration; however, the result was not significant, probably because of the small sample size and the selected conditions [24]. H. pylori infection was found to have a substantial negative impact on metabolic control in children and adolescents with T1DM [26,35]. Dai et al. reported that H. pylori infection was positively correlated with HbA1c levels and worse glycemic control in adolescents and children with T1DM [36]. These findings indicated a notable link between H. pylori infection and increased levels of HbA1c, as well as the duration of T1DM.
A meta-analysis by Feng Wang, who included 39 eligible studies from 1997 to 2012, showed a significant association between H. pylori infection and an increased risk of both T1DM and T2DM [37]. In another meta-analysis by Kamyar Mansori on 41 studies with 9559 individuals from 1990 to 2019, there was a significant association between H. pylori infection and the risk of developing diabetes, particularly T2DM, in the subgroup analysis [38]. Similarly, this present meta-analysis found a positive association between T1DM and H. pylori infection, although it did not reach statistical significance. Another study revealed that H. pylori infection was not significantly associated with T1DM in children and that the glycemic control in these patients was similar between those who developed H. pylori infection and those who did not [34]. The potential association between H. pylori infection and T1DM remains a topic of debate, particularly in terms of glycemic control, gastrointestinal symptoms, infection prevalence, eradication and reinfection rates, and sanitary conditions [29]. In this meta-analysis, we performed an extensive and up-to-date literature search to identify a significant number of studies that provided sufficient data from 2797 pediatric individuals from 1997 to 2020 and found a positive correlation of H. pylori infection with HbA1c levels and T1DM duration. Indeed, this meta-analysis had a relatively large sample size, and none of the included studies had an individual substantial influence on the overall results.
Based on our findings, an alternative inference was the impact of DM on the incidence of H. pylori infection. Therefore, this infection might be a complication rather than a cause of T1DM. This result could be attributed to the fact that in individuals with diabetes, reduced gastric motility and peristaltic activity might facilitate H. pylori colonization [39]. Infection with H. pylori increases the production of proinflammatory cytokines, which may lead to impaired glycemic control [40]. Furthermore, chemical changes, such as the nonenzymatic glycosylation of mucins, in the gastric mucosa and elevated sialic acid levels may act as receptors on cell surfaces and facilitate the adhesion of H. pylori to gastric mucosa cells [41,42,43]. In addition, impaired nonspecific immunity further contributes to the risk of H. pylori infection in patients with diabetes [41].
Several mechanisms that can explain the association between H. pylori infection and the risk of diabetes have been proposed. One mechanism involves inflammatory cytokines, which can induce the phosphorylation of serine residues on the insulin receptor substrate. This phosphorylation may impair the interaction between the substrate and the insulin receptors, leading to impaired insulin function [44]. Furthermore, H. pylori infection induces inflammation, which affects the pancreatic β cells and leads to decreased insulin secretion. In particular, cag+ strains of H. pylori can further reduce insulin secretion by affecting the production of somatostatin [38,45]. Another mechanism involves lipopolysaccharides (LPSs), which are produced by Gram-negative bacteria, such as H. pylori. LPSs can activate Toll-like receptors, resulting in insulin resistance [46]. Moreover, H. pylori infection has been associated with elevated leptin and ghrelin levels, which can contribute to obesity and increase the risk of developing diabetes [47].
These events collectively contribute to poor blood sugar control during the development of diabetes mellitus. In this study, H. pylori infection was not significantly associated with age at T1DM diagnosis, but it had a noteworthy correlation with prolonged T1DM duration and HbA1c level. These findings imply that although H. pylori might not affect the age of initial T1DM diagnosis, it could influence the progression of T1DM. It is plausible that over time, impaired glucose metabolism in patients with T1DM could facilitate H. pylori colonization, suggesting that a vicious cycle of H. pylori infection and impaired glucose control facilitates T1DM development. Nevertheless, further research is essential to fully comprehend the underlying mechanisms.
The studies included in this meta-analysis used a variety of diagnostic methods (e.g., the urea breath test; measurement of IgA, IgG, and IgM antibodies for H. pylori; the detection of H. pylori antigens in stool samples; and the measurement of cagA IgG antibodies) for H. pylori infection. This might have contributed to the divergent findings on this topic. Of the 12 case–control studies, 8 used an enzyme-linked immunosorbent assay to detect H. pylori antibodies. Notably, serologic methods cannot differentiate between recent and previous infections. In one study, detection of fecal H. pylori antigens was found to potentially offer greater relevance in identifying active gastrointestinal infection in specific patients with diabetes [48]. Therefore, future studies should include multiple tests to provide more comprehensive and reliable results.
Clinically, the ESPGHAN/NASPGHAN and JSPGHAN guidelines for the management of H. pylori in children and adolescents recommend against treating H. pylori without peptic ulcer disease, gastric mucosa-associated lymphoid tissue lymphoma, or chronic idiopathic thrombocytopenia purpura. However, we found that H. pylori was associated with relatively high HbA1c levels and long duration of diabetes. Therefore, we recommend that H. pylori infection should be considered in pediatric cases of T1DM with poor blood sugar control. We hypothesized that H. pylori may exert this influence through a toxin-associated mechanism, because it is known to produce some toxins secondary to inflammation, cytokine reaction, and autoimmune disease.
The current study had several limitations. First, there was no information on the history of drug or nondrug treatments, which can affect the presence of H. pylori infection and the development of metabolic syndrome and insulin resistance. Future studies should consider evaluating the impact of different treatments on these outcomes in individuals with H. pylori infection. Second, gastrointestinal comorbidities, such as celiac disease, were not considered; these should also be addressed in future studies. Third, the current study focused on patients with T1DM and did not compare the association between H. pylori infection and HbA1c levels between patients with T1DM and those with T2DM. Therefore, future studies should include patients with T2DM to facilitate a more comprehensive analysis and provide valuable insights on the different types of diabetes. Fourth, our study did not have access to a dataset from Asian populations, thereby limiting the generalizability of our findings to this group; future research should include datasets from Asia. Fifth, although case–control studies can provide valuable insights on associations, they have inherent limitations, such as recall and selection biases. Therefore, the design and implementation of cohort studies could yield a more comprehensive and detailed assessment of the association between H. pylori infection and diabetes.

5. Conclusions

Notably, the subgroup analysis found a significant and positive link of H. pylori infection with HbA1c level and diabetes duration. These results imply that chronic conditions that result in disrupted glycemic control and prolonged disease duration have a potential influence on the susceptibility to H. pylori infection.
For a more comprehensive understanding and to obtain robust evidence, the next step would entail large-scale cohort studies with substantial sample sizes; rigorous methodologies that take into account factors such as weight loss, socioeconomic status, and household size; and the inclusion of worldwide populations. Such studies could yield more explicit insights and enhance our comprehension of the complex interplay between H. pylori infection and diabetes outcomes, thereby paving the way for more targeted interventions and improved management strategies for both H. pylori infection and diabetes-related complications. Nevertheless, the findings of this meta-analysis suggest that pediatric patients with relatively long T1DM duration and poor glycemic control should be screened for H. pylori infection.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/medicina60010119/s1, Figure S1: Correlation analysis of H. pylori infection and age at diagnosis of T1DM.; Figure S2: (A) Sensitivity analysis for the study; (B) Sensitivity analysis for Age; (C) Sensitivity analysis for duration of diabetes; (D) Sensitivity analysis for HbA1c level.

Author Contributions

Conception: W.-K.C. and S.-W.H.; Methodology: W.-K.C. and Y.-K.H.; Formal analysis and Interpretation: Y.-K.H.; Drafted the manuscript: W.-K.C.; Critically revised the manuscript: S.-W.H., H.-C.F., and W.-H.T.; Gave final approval: all authors. All authors have read and agreed to the published version of the manuscript.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data of this study are available on request from the corresponding authors, H.C.F. and W.H.T.

Conflicts of Interest

The authors declare no conflicts of interest.

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Medicina 60 00119 g001
Figure 1. A PRISMA flowchart showing the study selection and inclusion process.
Figure 1. A PRISMA flowchart showing the study selection and inclusion process.
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Figure 2. Funnel plot analysis of H. pylori infection and Type 1 diabetes mellitus.
Figure 2. Funnel plot analysis of H. pylori infection and Type 1 diabetes mellitus.
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Figure 3. Correlation analysis of H. pylori infection and Type 1 diabetes mellitus [23,24,25,26,27,28,29,30,31,32,33,34].
Figure 3. Correlation analysis of H. pylori infection and Type 1 diabetes mellitus [23,24,25,26,27,28,29,30,31,32,33,34].
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Figure 4. Correlation analysis of H. pylori infection and diabetes duration [24,26,29,30,31,33,34].
Figure 4. Correlation analysis of H. pylori infection and diabetes duration [24,26,29,30,31,33,34].
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Figure 5. Correlation analysis of H. pylori infection and hemoglobin A1c levels [26,29,30,31,33,34].
Figure 5. Correlation analysis of H. pylori infection and hemoglobin A1c levels [26,29,30,31,33,34].
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Table 1. The main charateristics of included studies and the relation between H. pylori and Diabetes.
Table 1. The main charateristics of included studies and the relation between H. pylori and Diabetes.
AuthorYearNationStudy DesignSample SizeGender (Male/Female)AgeControl GroupMeasurement of Association
Odds Ratio (95% C.I.)		Type of Diabetes
(Mean of HbA1c)
(Duration)		H. pylori
Test Method		Control Var.
M Pocecco, et al. [23]1997ItalyCase-Control Study379
(Control: 310; Case: 69)		213/16616Admitted for minor extra-abdominal surgery with no history of abdominal pain 6.08
(2.94, 12.58)		DM
(-)
(-)		ELISAAge, sex, education and economic status
S Salardi, et al. [24]1999ItalyCase-Control Study339
(Control: 236; Case: 103)		N/A12Patients attending the hospital for minor endocrine disorders1.79
( 0.93, 3.44)		T1DM
(-)
(4.96 ± 3.22 years)		RIBASIAAge
Arslan D., et al. [25]2000TurkeyCase-Control Study130
(Control: 42; Case: 88)		N/A12Healthy children2.80
(1.29 to 6.10)		T1DM
(11.08 ± 3.17)
(3.85 Years)		ELISA-
Marcello Candelli, et al. [26]2003ItalyCase-Control Study268
(Control: 147; Case: 121)		145/12314.96Healthy participants0.98
(0.58, 1.66)		T1DM
(8.2 ± 1.4 )
(79.7 ± 55.5 months)		C-UBTAge, sex, and social class
Krause I, et al. [27]2009ColombiaCase-Control Study197
(Control: 140; Case: 57)		N/A16Healthy subjects3.35
(1.72, 6.53)		T1DM
(-)
(8.8 ± 8.7 years)		 ELISA-
Cabral VL, et al. [28]2009BrazilCase-Control Study45
(Control: 30; Case: 15)		N/A17.6Adolescents with the histological findings of gastric and duodenal biopsies with normal mucosal architecture0.38
(0.10, 1.39)		T1DM
(-)
(8 ± 3.6 years)		Rapid Urease Test-
El-Eshmawy M.M., et al. [29]2011EgyptCase-Control Study242
(Control: 80; Case: 162)		108/13419.49Healthy subjects3.58
(2.01, 6.39)		T1DM
(8.2 ± 1.75)
(7.29 ± 7.9 years)		ELISAAge, sex and socioeconomic status
Zekry O.A., et al. [30]2013EgyptCase-Control Study120
(Control: 60; Case: 60) 		N/A12.53Healthy children who were selected from among relatives2.4
(1.25,4.58)		T1DM
(-)
(-)		ELISAAge, sex and socioeconomic
Agata Chobot, et al. [31]2014PolandCase-Control Study447
(Control: 298; Case: 149)		201/24613.4Healthy children and adolescents0.65
(0.36, 1.18)		T1DM
(7.69 ± 1.63 )
(4.6 ± 3.5 years)		C-UBTAge and sex
Samah M Osman, et al. [32]2016SudanCase-Control Study180
(Control: 90; Case: 90)		96/841-18Healthy children0.95
(0.51, 1.76)		T1DM
(-)
(duration < 6 month)		ELISAAge and sex
Hassan Bazmamoun, et al. [33]2016IranCase-Control Study160
(Control: 80; Case: 80)		63/979.37Non-Diabetic children from the same clinic2.25
(1.20 to 4.24)		T1DM
(-)
(2.14 ± 0.43)		EIA TestAge, sex and socioeconomic status
Esmaeili Dooki MR, et al. [34]2020IranCase-Control Study168
(Control: 105 ; Case: 63)		81/8710.44Children without Diabetes Mellitus1.18
(0.58, 2.42)		T1DM
(-)
(at least 6 months)		 Stool TestAge and gender
N/A: Not available.
Table 2. Characteristic of Diabetic patients.
Table 2. Characteristic of Diabetic patients.
AuthorYearNationStudy DesignSample SizeGender (Male/Female)Diabetic-Age (Year)Diabetic-HbA1c (%)Diabetic-Duration (Year)
HP+HP−HP+HP−HP+HP−
M Pocecco, et al. [23]1997ItalyCase-Control Study6942/2716117.67.132
S Salardi, et al. [24]1999ItalyCase-Control Study103N/A13.2 ± 3.411.2 ± 3.4N/AN/A6 ± 3.44.3 ± 3.2
Arslan D., et al. [25]2000TurkeyCase-Control Study88N/AN/AN/AN/AN/AN/AN/A
Marcello Candelli, et al. [26]2003ItalyCase-Control Study12165/5616 ± 5.614.3 ± 5.58.05 ± 4.527.9 ± 108.05 ± 4.525.35 ± 4.09
Krause I, et al. [27]2009ColombiaCase-Control Study5724/33N/AN/AN/AN/AN/AN/A
Cabral VL, et al. [28]2009BrazilCase-Control Study156/91817N/AN/A710
El-Eshmawy M.M., et al. [29]2011EgyptCase-Control Study16272/9020.1 ± 4.619.8 ± 4.348.3 ± 1.586.8 ± 2.38.9 ± 8.64.22 ± 2.35
Zekry O.A., et al. [30]2013EgyptCase-Control Study60N/A12.0 ± 2.412.89 ±2.297.75 ± 1.675.72 ±1.29.25 ± 2.736.11 ± 1.78
Agata Chobot, et al. [31]2014PolandCase-Control Study14967/8213.3 ± 3.313.9 ±3.67.82 ± 1.427.60 ± 1.665.3 ± 3.94.4 ± 3.4
Samah M Osman, et al. [32]2016SudanCase-Control Study9050/40N/AN/AN/AN/AN/AN/A
Hassan Bazmamoun, et al. [33]2016IranCase-Control Study8032/487.7 ± 0.867.58 ± 0.658 ± 0.657.9 ± 0.402.72 ± 0.551.26 ± 0.13
Esmaeili Dooki MR, et al. [34]2020IranCase-Control Study6334/298.84 ± 2.037.45± 2.98.08 ± 1.517.9 ± 0.402.74 ± 1.623.16 ± 2.57
N/A: Not available.
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Chua, W.-K.; Hong, Y.-K.; Hu, S.-W.; Fan, H.-C.; Ting, W.-H. A Significant Association between Type 1 Diabetes and Helicobacter pylori Infection: A Meta-Analysis Study. Medicina 2024, 60, 119. https://doi.org/10.3390/medicina60010119

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Chua W-K, Hong Y-K, Hu S-W, Fan H-C, Ting W-H. A Significant Association between Type 1 Diabetes and Helicobacter pylori Infection: A Meta-Analysis Study. Medicina. 2024; 60(1):119. https://doi.org/10.3390/medicina60010119

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Chua, Wei-Kian, Yi-Kai Hong, Shu-Wei Hu, Hueng-Chuen Fan, and Wei-Hsin Ting. 2024. "A Significant Association between Type 1 Diabetes and Helicobacter pylori Infection: A Meta-Analysis Study" Medicina 60, no. 1: 119. https://doi.org/10.3390/medicina60010119

APA Style

Chua, W. -K., Hong, Y. -K., Hu, S. -W., Fan, H. -C., & Ting, W. -H. (2024). A Significant Association between Type 1 Diabetes and Helicobacter pylori Infection: A Meta-Analysis Study. Medicina, 60(1), 119. https://doi.org/10.3390/medicina60010119

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