The remarkable geographical pattern of gastric cancer mortality in Ecuador

Cancer Epidemiol. 2017 Dec:51:92-97. doi: 10.1016/j.canep.2017.10.014. Epub 2017 Nov 5.

Abstract

Aim: This study was aimed to describe the gastric cancer mortality trend, and to analyze the spatial distribution of gastric cancer mortality in Ecuador, between 2004 and 2015.

Methods: Data were collected from the National Institute of Statistics and Census (INEC) database. Crude gastric cancer mortality rates, standardized mortality ratios (SMRs) and indirect standardized mortality rates (ISMRs) were calculated per 100,000 persons. For time trend analysis, joinpoint regression was used. The annual percentage rate change (APC) and the average annual percent change (AAPC) was computed for each province. Spatial age-adjusted analysis was used to detect high risk clusters of gastric cancer mortality, from 2010 to 2015, using Kulldorff spatial scan statistics.

Results: In Ecuador, between 2004 and 2015, gastric cancer caused a total of 19,115 deaths: 10,679 in men and 8436 in women. When crude rates were analyzed, a significant decline was detected (AAPC: -1.8%; p<0.001). ISMR also decreased, but this change was not statistically significant (APC: -0.53%; p=0.36). From 2004 to 2007 and from 2008 to 2011 the province with the highest ISMR was Carchi; and, from 2012 to 2015, was Cotopaxi. The most likely high occurrence cluster included Bolívar, Los Ríos, Chimborazo, Tungurahua, and Cotopaxi provinces, with a relative risk of 1.34 (p<0.001).

Conclusion: There is a substantial geographic variation in gastric cancer mortality rates among Ecuadorian provinces. The spatial analysis indicates the presence of high occurrence clusters throughout the Andes Mountains.

Keywords: Disease mapping; Geographic information systems; Jointpoint; Spatial scan statistics; Stomach neoplasms.

MeSH terms

  • Aged
  • Ecuador
  • Female
  • Geography
  • Humans
  • Male
  • Middle Aged
  • Stomach Neoplasms / epidemiology
  • Stomach Neoplasms / mortality*
  • Survival Analysis