Stomach, Esophageal, and Lung Cancer Mortality Risk and Their Shared Risk Factors in Iran: A County-Level Spatial...

Disease mapping has a long history in epidemiology. Evaluating the spatial pattern of several diseases, as well as shared and specific risk factors in mortality, is considered one of the applications of disease mapping. Stomach, esophageal, and lung cancers are among the five most common cancers among both genders in Iran. The present study aimed to investigate the geographical distribution of the relative risk of mortality and to define the spatial pattern of shared and specific risk factors for the three cancers mentioned above by sharing their mortality data at the province and county levels in Iran.

In this ecological study, the mortality data of stomach, esophageal, and lung cancers were analyzed in Iran from March 2013 to March 2015. The Besag, York, and Mollie's (BYM) and shared component (SC) models were used to compare the spatial variations of the relative risks of those cancers by applying OpenBUGS version 3.2.3 and R version 3.6.3.

The number of deaths from esophageal, stomach, and lung cancers in Iran during March 2013-March 2014 was 11,720, of which stomach and lung cancers were 50% and 30%, respectively. In this period, stomach, esophageal, and lung cancer mortality rates were 9, 2, and 7 per 100,000 individuals, respectively. The spatial pattern of the stomach and esophageal cancer mortality was more similar to lung cancer due to the risk factors shared only between esophageal and stomach cancers. The relative risk for esophageal and stomach cancers was significantly higher in the northern half of Iran than in the southern half. However, the dispersion of the relative risk of lung cancer was higher than the other two cancers. The highest RR for esophageal, stomach, and lung cancers were in West Azerbaijan and East Azerbaijan provinces. The lowest relative risk for esophageal and stomach cancers was Hormozgan and for lung cancer was Ilam.

Some differences were observed in the achieved patterns of provinces and counties, the most significant factor of which was related to considering smaller areas. As indicated in this study, high-risk areas can be identified easier by analyzing and mapping the diseases on a smaller scale and more accurate, less expensive, and faster health policies, and plans can be adopted to identify and reduce the risk factors related to diseases.