Introduction: A wide range of factors affect public health and subsequent health status of people is different in different social classes. Nowadays by high acceleration of changes in influencing factors in exacerbation of cancer incidence is predicted to accelerate cancer growth rate and will be more than double the current situation in the next two decades and is considered as a challenge for health systems. The purpose of this study was to investigate the relationship between gastric cancer in men in all provinces of the country and their socio-economic status.

Materials & methods: Drawback of traditional methods for estimating cancer rates is that the coefficients may change with time and for a management system of factors affecting on cancer, in terms of its dynamics, will lose its efficiency. Therefore, applying advanced techniques such as neural networks can be effective in estimating the non-linear and dynamic systems. Socioeconomic data were collected from provincial statistical yearbooks and Data on age-standardized incidence rate (ASIR) of gastric cancer per 100,000 populations stratified by sex were obtained from published reports by Iran Cancer Registry. This study included the combination of sections (all provinces) and the period 2004-2009. MATLAB software was used for data analysis.

Findings: The results showed that socio-economic factors are significantly associated with gastric cancer. Directly relationship of unemployment and family size, and inverse relationship of literacy rate, urbanization ratio and household expenditure with cancer incidence rate are evident in this study.

Discussion & Conclusion: The socioeconomic inequalities in incidence of gastric cancer in Iranian men, requires investigating preventable mechanisms and supporting healthy lifestyles among deprived provinces. In general, this neural network model and non-linear system which obtained from that, can be used to determine the rate incidence of gastric cancer based on the input data in any province or any of the new solar year. This information can be used in planning for prevention and management of cancer incidence rates.