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Biomass cookstove food preparation is linked to aero-digestive cancers, mediated by ingested and inhaled carcinogens (e.g., heterocyclic amines, and polycyclic aromatic hydrocarbons). We investigated the association between gastric adenocarcinoma, wood cookstove use, H. pylori CagA infection and risk modification by variants in genes that metabolize and affect the internal dose of carcinogens. We conducted a population-based, case–control study (814 incident cases, 1049 controls) in rural Honduras, a high-incidence region with a homogeneous diet and endemic H. pylori infection, primarily with the high-risk CagA genotype. We investigated factors including wood cookstove use, H. pylori CagA serostatus, and 15 variants from 7 metabolizing genes, and the interactions between wood stove use and the genetic variants. Male sex (OR 2.0, 1.6–2.6), age (OR 1.04, 1.03–1.05), wood cookstove use (OR 2.3, 1.6–3.3), and CagA serostatus (OR 3.5, 2.4–5.1) and two SNPs in CYP1B1 (rs1800440 and rs1056836) were independently associated with gastric cancer in multivariate analysis. In the final multivariate model, a highly significant interaction (OR 3.1, 1.2–7.8) was noted between wood cookstove use and the rs1800440 metabolizing genotype, highlighting an important gene-environment interaction. Lifetime wood cookstove use associates with gastric cancer risk in the high-incidence regions of Central America, and the association is dependent on the rs1800440 genotype in CYP1B1. H. pylori CagA infection, wood cookstove use and the rs1800440 genotype, all of which are highly prevalent, informs who is at greatest risk from biomass cookstove use. [ABSTRACT FROM AUTHOR]

Background: Geospatial technology has facilitated the discovery of disease distributions and etiology and helped target prevention programs. Globally, gastric cancer is the leading infection-associated cancer, and third leading cause of cancer mortality worldwide, with marked geographic variation. Central and South America have a significant burden, particularly in the mountainous regions. In the context of an ongoing population-based case-control study in Central America, our aim was to examine the spatial epidemiology of gastric cancer subtypes and H. pylori virulence factors., Methods: Patients diagnosed with gastric cancer from 2002 to 2013 in western Honduras were identified in the prospective gastric cancer registry at the principal district hospital. Diagnosis was based on endoscopy and confirmatory histopathology. Geospatial methods were applied using the ArcGIS v10.3.1 and SaTScan v9.4.2 platforms to examine regional distributions of the gastric cancer histologic subtypes (Lauren classification), and the H. pylori CagA virulence factor. Getis-Ord-Gi hot spot and Discrete Poisson SaTScan statistics, respectively, were used to explore spatial clustering at the village level (30-50 rural households), with standardization by each village's population. H. pylori and CagA serologic status was determined using the novel H. pylori multiplex assay (DKFZ, Germany)., Results: Three hundred seventy-eight incident cases met the inclusion criteria (mean age 63.7, male 66.3%). Areas of higher gastric cancer incidence were identified. Significant spatial clustering of diffuse histology adenocarcinoma was revealed both by the Getis-Ord-GI* hot spot analysis (P-value < 0.0015; range 0.00003-0.0014; 99%CI), and by the SaTScan statistic (P-value < 0.006; range 0.0026-0.0054). The intestinal subtype was randomly distributed. H. pylori CagA had significant spatial clustering only in association with the diffuse histology cancer hot spot (Getis-Ord-Gi* P value ≤0.001; range 0.0001-0.0010; SaTScan statistic P value 0.0085). In the diffuse gastric cancer hot spot, the lowest age quartile range was 21-46 years, significantly lower than the intestinal cancers (P = 0.024)., Conclusions: Geospatial methods have identified a significant cluster of incident diffuse type adenocarcinoma cases in rural Central America, suggest of a germline genetic association. Further genomic and geospatial analyses to identify potential spatial patterns of genetic, bacterial, and environmental risk factors may be informative.