Geospatial analysis of Helicobacter pylori infection in South Australia: Should location influence eradication therapy?

Abstract

Background and aim: Rates of antimicrobial-resistant Helicobacter pylori infection are rising globally; however, geospatial location and its interaction with risk factors for infection have not been closely examined.

Methods: Gastric biopsy specimens were collected to detect H. pylori infection at multiple centers in Adelaide, South Australia, between 1998 and 2017. The geospatial distribution of antibiotic-resistant H. pylori in the Greater Adelaide region was plotted using choropleth maps. Moran's I was used to assess geospatial correlation, and multivariate linear regression (MLR) was used to examine associations between migration status, socioeconomic status, age, gender, and rates of H. pylori positivity and antibiotic resistance. Geographically weighted regression (GWR) was used to determine the extent to which the associations varied according to geospatial location.

Results: Of 20 108 biopsies across 136 postcodes within the Greater Adelaide region, 1901 (9.45%) were H. pylori positive. Of these, 797 (41.9%) displayed clarithromycin, tetracycline, metronidazole, or amoxicillin resistance. In MLR, migration status was associated with the rate of H. pylori positivity (β = 3.85% per 10% increase in a postcode's migrant population; P < 0.001). H. pylori positivity and resistance to any antibiotic were geospatially clustered (Moran's I = 0.571 and 0.280, respectively; P < 0.001 for both). In GWR, there was significant geospatial variation in the strength of the migrant association for both H. pylori positivity and antibiotic resistance.

Conclusion: Our study demonstrates the heterogeneous geospatial distribution of H. pylori positivity and antibiotic resistance, as well as its interaction with migrant status. Geographic location and migrant status are important factors to consider for H. pylori eradication therapy.

Keywords: Helicobacter pylori; antibiotics; antimicrobial; antimicrobial resistance; geospatial; resistance.

Figure 1

The boundary and 185 postcodes of the Greater Adelaide Planning Region. [Color figure can be viewed at wileyonlinelibrary.com]

Figure 2

Change in rates of antibiotic resistance amongst those positive for Helicobacter pylori by year. •••, Amoxicillin; •••, tetracycline; •••, clarithromycin; •••, metronidazole; •••, overall. •••, N tested. [Color figure can be viewed at wileyonlinelibrary.com]

Figure 3

Choropleth map of antibiotic resistance rates amongst those subjects positive for Helicobacter pylori by Greater Adelaide Planning Region postcode 1998–2018. [Color figure can be viewed at wileyonlinelibrary.com]

Figure 4

Choropleth map of migrant rates by postcode in the Greater Adelaide Planning Region for 1998–2018. [Color figure can be viewed at wileyonlinelibrary.com]

Figure A1

Flow chart of patients undergoing upper gastrointestinal endoscopy. [Color figure can be viewed at wileyonlinelibrary.com]

Figure A2

Change in rates of Helicobacter pylori positivity by year. •••, H. pylori positive. •••, N tested. [Color figure can be viewed at wileyonlinelibrary.com]

Figure A3

Choropleth map of Helicobacter pylori positivity rates by Greater Adelaide Planning Region postcode, 1998–2018. [Color figure can be viewed at wileyonlinelibrary.com]

Figure A4

Choropleth map of the postcode‐level coefficients and R ² from the geographically weighted regression of Helicobacter pylori positivity rates. Each plot represents the regression coefficient between H. pylori and the demographic variable within each postcode. All 136 postcodes showed a significant migrant density‐to‐H. pylori association (P < 0.05), with the strength of the association varying from a 2.65% to 4.15% increase in the absolute rate of H. pylori per 10% increase in the migrant density. The color bar indicates the value of the local coefficient or R ² statistic. SEIFA, Socioeconomic Index For Areas. [Color figure can be viewed at wileyonlinelibrary.com]

Figure A5

Choropleth map of the postcode‐level coefficients and R ² from the geographically weighted regression of rates of antibiotic resistance. Each plot represents the regression coefficient between antibiotic resistance and the demographic variable within each postcode. All 136 postcodes showed a significant migrant density‐to‐Helicobacter pylori association (P < 0.05), with the strength of the association varying from a 1.22% to 1.79% increase in the absolute rate of antibiotic resistance per 10% increase in the migrant density. The color bar indicates the value of the local coefficient or R ² statistic. SEIFA, Socioeconomic Index For Areas. [Color figure can be viewed at wileyonlinelibrary.com]