Geographical variation and factors associated with gastric cancer in Manitoba
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Date
2019
Authors
Fakanye, Oluwagbenga
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Abstract
Introduction: Gastric cancer (GC) is one of the deadliest diseases as most of the cases are diagnosed at late stages, thereby making treatment almost impossible. GC incidence in North America has been reported to be decreasing over the years. Nevertheless, the primary concern is whether the decrease is valid for all communities?
Purpose and Objectives: The purpose of this study is to identify high-risk GC hotspots in Manitoba and investigate factors associated with GC in Manitoba. The objectives were to (1) describe and investigate the geographical variation of GC incidence in Manitoba; (2) explore factors influencing the geographic change of GC incidence in Manitoba, and (3) investigate the geographical variation of GC incidence over time in Manitoba.
Methods: This research study adopted an ecological design. A spatial Poisson regression model was used to address research objectives (1) and (2), and a Spatio-temporal Poisson regression model was used to address research objective 3.
Results: SESI was significantly associated with cardia gastric cancer (CGC) and marginally associated with non-cardia gastric cancer (NCGC), while the Indigenous population proportion was marginally associated with CGC. In specific, 1 unit increase in SESI reduces the risk of CGC by 14% (IRR= 0.859; 95% CI: 0.780 - 0.947) and the risk of NCGC by approximately 10% (IRR = 0.898; 95% CI: 0.812 – 0.995); 1% increase in regional Indigenous population proportion reduces the risk of CGC by 1.4% (IRR = 0.986; 95% CI: 0.978 – 0.994). Also, 1 unit increase in SESI reduces the risk of CGC among women by 26.2% (IRR = 0.738; 95% CI: 0.618 – 0.879), and a 1% increase in Indigenous population proportion reduces the risk of CGC among women by 1.9% (IRR = 0.981; 95% CI: 0.966 – 0.996).
Conclusion: This study has demonstrated the existence of regional variation of GC incidence risk with temporal pattern in Manitoba.
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Keywords
spatial model, Spaio-temporal model, Gastric cancer, Stomach cancer, Epidemiology of gastric cancer