Role of Time in Spatial Analysis of Diseases in Tehran

Changes in socio-economic trends and factors that affect on the health of a society as well as changes of environmental that occur over time, can alter the effects of a disease at different times. At the level of city, Identify regions with high risk of getting a particular disease that can be lead to death, Compared to other regions and investigate the behavior of any of these diseases during different time periods, an important role in disease control and health management in the community. In this study, investigated the trends of disease-based mortality in different regions of Tehran with revolving around seasonal and annual changes during the period 1993-2013. Geostatistical analysis using different tools to assess the relationship between disease at a certain time and in one place with the surrounding area. The Local Moran's I index is Including neighborhood analysis tools that to assess disease in specific time and place are effective to neighboring regions and find the neighborhood at different times, to identified regions of high risk (HOT SPOT). Moran index value articulated the relationship of a variable and its distribution in space and time with neighboring regions. diseases of Hot Spots and classification them in spatial clusters on the basis of this index, can be identified. Neighborhood is defined in such a way that at the level of a city is different for various diseases. This optimum amount neighborhood may be affected at different time intervals depending on the nature of the disease and also affected it is different from local factors or global. Results of the analysis on 12 group’s mortality disease-based showed that spatial significant levels are different in each disease. The relationship between diseases in different regions may be clustered in regions or dispersion they exist. This amounts to 5 groups of diseases, including diseases of the brain, liver, gastrointestinal and bleeding, cancer and stomach cancer have a meaningful relationship with the spatial factor’s in Scaling throughout a city. It is worth mentioning that This relationship may be different in larger scale than the area of the city. In the next stage, using temporal of analysis for five groups of diseases that have higher spatial index, Amount dependence of any of the diseases during the time periods of annual and also examined changes of any disease in different season . The results showed is different neighborhood radius for different diseases in different seasons. Also regions with a high risk of each disease being different with the change of seasons and changing environmental parameters. In examined the results of annual trends showed that during twenty year period, Amount dependence of any of the diseases to locations due to changes In socio-economic status and health of the community is quite different.