Understanding the level of development and analyzing inequalities in various geographical areas and economic sectors is a tool for more appropriate and balanced planning and policymaking. In this regard, the aim of the present research was comparative analysis of the agricultural development in the COUNTIES of MAZANDARAN province, one of the most important areas for agricultural and livestock production in the country, using the Composite Index (CI) method. By systematically reviewing the literature and selecting 52 indicators across five dimensions of the agricultural system, animal husbandry, agricultural institutions and industries, crop farming, horticulture, and agricultural mechanization were identified and necessary data were obtained from valid statistical sources. The indicators were normalized using the method of division by the mean, and for selecting the weights of dimensions and indicators, the Analytic Network Process (ANP) technique was employed based on the opinions of agricultural experts in MAZANDARAN Province. The results of the CI showed that the COUNTIES of Amol, Sari, and Joybar obtained the highest development scores. Additionally, cluster analysis results indicated that only 14% of the COUNTIES in the province, including Amol, Joybar, and Sari, belonged to the developed category. Furthermore, 23% of the COUNTIES, including Babol, Babolsar, Behshahr, Qaemshahr, and Fereydunkenar were developed, relatively. The results also showed that about 27% COUNTIES including Ramsar, Mahmoudabad, Nur, Tonekabon, Abbasabad, and Kelardasht were less developed. It should also be mentioned that 36% of COUNTIES, including Chalus, Savadkooh, North Savadkooh, Simorgh, Galugah, Miandorud, Neka, and Nowshahr were categorized within undeveloped COUNTIES in terms of agricultural development composite index. In this study, to demonstrate the spatial analysis of the agricultural development status, a geographic information system was used. Based on the research data, it is necessary to pay attention to the agricultural development in COUNTIES with low development levels by policy-makers, planners, and implementers of agricultural development at the national and provincial levels.

In current research, the main objective is to determine the necessity requirements of establishing agricultural activities using hierarchical analysis method. Due to special climate and location conditions and resulting potentials from these conditions in MAZANDARAN province, agricultural activities are of the most important activities being done in this province. Each of these COUNTIES, have suitable or unsuitable conditions in accepting activities related to agriculture section, in which determining their level and their ability rank, is an important source for distribution of services and activities related to agriculture in the territory. Therefore, determination of related and accessible indicators in doing agricultural activities are done. Then the ability of COUNTIES of province in accepting farming activities as a subsection of agriculture based on specific indicators, was determined and available alternations in land exploitation and the intensity of its use in agriculture section were determined.

The increase in urbanization trend and environmental, social and demographical consequences has led to the reaction of health city’s advocates focusing on health and sanitation of human society. Therefore, in the middle of 1980, health city approach was proposed as a way of achieving individual and social desirable life. The aim of this research is Spatial Analysis of Health City Indicators Situation. The research methodology is descriptive-analytical and based on secondary formal data. In this study, fuzzy clustering analysis (C-Means algorithm) was used to cluster cities in MAZANDARAN and for more accuracy Topsis model was used. The results show that cities membership is independent of spatial factor of distance from center. Also, cities membership in fourth cluster rejected probability of difference between west, center and east cities in province. On the other hand, albeit it was supposed that center county’s cities are in a better condition in comparison to other COUNTIES, it was not the case and they got the seventh rank.

Mississippi has one of the highest stroke mortality rates in the nation. This paper present results of 2005 and 2006 surveys undertaken in an intervention and control county in rural Mississippi. A random-digit-dial (RDD) telephone surveys were conducted on adults 18 and older sampled from the civilian, non-institutionalized populations of Warren (control) and Washington (intervention) COUNTIES before and after implementing a 6-month long stroke awareness educational campaign in Washington County. The analyzed results indicate that response rates to several of the questions increased after the intervention in Washington County, the results of this small sample survey do not show sufficient evidence to support any effect of the intervention. A significant lesson learned from this effort is that a more specific target population must be selected for intervention, and much tailored messages and appropriate media must also be identified and implemented.

The issue of regional inequalities and deprivation is not only the problem in the affected areas, but it also have important consequences for the entire country. Imbalances in demographic and spatial proportions, inactivation of the potential of the affected region and so on, are very serious problems of regional inequalities. "Deprivation" is a term related to the imbalance in regional development. One of the most important features of the border areas, especially the coast, is their remoteness from the center of gravity of the motherland, which is generally shaped by the economic centers and the heart of the growth and development of governments. During identification of the deprived areas of the country that took place at different times, Bushehr and Hormozgan have always been among the most deprived provinces. While Bushehr province has the potential to be one of the most developed provinces in the country, with its special geopolitical location, massive oil and gas reserves, access to maritime transport, and so on. Hormozgan Province, in spite of access to free waters and existence of various harbors, has the potential to become a trading hub for export and import of the country. The purpose of this study is to identify the deprivation level of southern coastal provinces (Bushehr and Hormozgan Provinces) and evaluation of the indicators of deprivation dimensions. Indicators of investigation have been extracted from different economic, social, educational, health and housing components of theoretical literature. Due to the large number of indictors and sub-indicators, Factor Analysis method was used for data reduction purposes and Data Pooling method transformed numerous indicators into key components. Now comparisons between all COUNTIES of both provinces are possible which is implemented with various components and is based on data retrieved in the year 1996, 2006 and 2011. Then the same method is repeated using new components derived from Factor Analysis method and then composite deprivation indicators are determined. In order to assess new data series derived from Factor Analysis method, Cluster Analysis method is used to classify the COUNTIES of both provinces. Different dimensions of deprivation, changes in the rate of deprivation and changes of the level of deprivation indicators for every single county of both provinces are derived. The obtained results show that deprivation is more evident in Hormozgan Province and is more intense as it moves eastward. The analysis of the trends over the years 1996 to 2011 indicate that in recent years, deprivation has generally decreased and the number of rich COUNTIES has increased. However, this reduction has increased in the COUNTIES of Bushehr province and some of the eastern COUNTIES of Hormozgan province have experienced minimal improvement over the past years. The severity of deprivation in the educational and health dimensions of COUNTIES in both provinces are greater and social and economic indicators have better status. According to the 2011 data, Jask, Roudan and Minab COUNTIES, which are all in the Hormozgan province, were the most deprived COUNTIES and Bushehr, Bandr Abbas, Bandar Deilam and Bandar Lengeh were the most benefited ones among the COUNTIES of both provinces.

Introduction: Spatial inequality in developing countries is an issue of concern to many policy makers and researchers. It may have causes such as regional dualities, the outflow of capital and labor, the geographic concentration of poverty and deprivation, the lack of optimal and voluntary distribution of human resources, etc. Therefore, this study has investigated spatial inequality among the districts of Iran.Spatial inequality means unequal distribution of economic and social opportunities and facilities in space. Geographic space can be discussed in different formats. One of the most important formats, especially on a national scale, is the concept of region. Thus, regional inequality implies an imbalance in the spatial structure of regions and is manifested in differences in living conditions, economic inequalities, and levels of development. A review of the literature on inequality shows that regional social inequality is generally attributed to three main factors: economic development, social policy, and regional policy.Methods: To measure spatial inequality across COUNTIES, we used data from the 2016 General Population and H ousing Census and other related findings. According to the 2016 census, the country has 429 COUNTIES. Factor analysis was used to weight and combine the indicators and create the spatial inequality. Based on the factor analysis, five factors were formed from economic, social, environmental, population structure and population density, and finally the spatial inequality was created by combining the factors. To show the zoning and leveling of inequality in the COUNTIES, Arc Pro software was used.Findings: The results show that there is spatial inequality between the COUNTIES. This inequality, especially in economic and social indicators, is such that the COUNTIES in the border areas (with the exception of the northern regions) have higher spatial inequality than the COUNTIES in the center of the country. The regions with high inequality include the eastern half, especially the southeast and northeast, and then the west, northwest and southwest of the country. Among the indicators, the conditions are in favor of COUNTIES in border areas only in the index of population structure status. As for the environmental index, conditions are favorable in the western, northwestern and northern regions of the country.Conclusion: The results of this research show that we face spatial inequalities between the COUNTIES of the country. These inequalities exist in various dimensions such as social, economic, environmental, population structure and population density. Moreover, the regions of the country, which are often the border and peripheral regions of the country, have higher inequalities than the central regions of the country. Also, due to the fact that these areas are among the first emigration areas of the country, there is a need for attention and practical plans to solve the internal spatial inequalities of the country

With respect to integrated regional development, analysis of factors affecting the development of the COUNTIES, one of the most effective tools in planning. Educational indicators, Undoubtedly, one of the most important components to have equal opportunities in region. This study is searching the COUNTIES of Gilan province, according to the educational indicators, to determined the less developed areas, be a tool for urban planners to make better decisions.The methodology of this research is descriptive-analyctical; first, 9 group of educational variables determined, then considering of TOPSIS model, normalization, scale-out and weighting the indicators with using SPSS and Mac- Grahannan correlation coefficient, for the variables is obtained and finally,16 COUNTIES in Guilan, with using of TOPSIS model, considerng educational indicators were ranked. the result of this study show that, Rasht, Siyahkal, Rudbar and Rudsar, are developed.the high development of educational county in Guilan province is Rasht with C+ = 1 and 1st rank and lowest development, is Anzali with C+ = 0 and 16st rank.also,62.5 percent of COUNTIES at Guilan province, is ranked in underdevelopment level,12.5 percent is in the less development and 25 percent is in the developed group.