Journal of

Background and Aim: When there is a big difference among income groups in a society, public health and healthcare costs may be affected through multiple channels. The present study aimed to investigate the effects of inequality and poverty (and other socio-economic characteristics of communities) on public health indicators and the structure of cost payments. 
Materials and Methods: The present applied descriptive study has been conducted in 34 countries of the world (in terms of having regular data about income inequality) during 1995-2012 using a panel data approach. Eviews 9 software was used to estimate the models. The estimates were done in separate models for health indices and the related costs.
Results: Income inequality and poverty on the one hand reduce public health, and on the other hand increase people’s share of healthcare payments. Besides, the level of education promotes the community’s public health and reduces direct out-of-pocket and private payments. However, population density in large cities leads to the increase of private health expenditure and direct out-of-pocket payments.
Conclusion: On the path of economic development, we should pay special attention to income inequality among the members of society. Following inequality and higher relative poverty, mental and emotional problems deepen in society, and the health of individuals is seriously damaged. Byweakening the efficient management of health sector, this issue increases the individuals’ direct out-of-pocket payments and, therefore, doubly deteriorates public health.

Background and Aim: Health and equal access to quality care regardless of age, gender, race and location is health systems' goal in all countries. This study aimed to determine inequality in healthcare services distribution and development level of cities in Guilan province.
Materials and Methods: This descriptive, cross-sectional study assessed the distribution state of 13 healthcare indicators in all cities of Guilan (n=16) in year 2011 and 2013. In order to collect data, the database of Statistical Center of Iran (SCI) was used as reference. The taxonomy technique was employed to determine the degree of development of different cities. In addition, indicators were weighed by Shannon’s entropy. Finally, TOPSIS was used to rank the cities in term of access to health sector resources.
Results: Taxonomy technique in 2 years showed that Rudbar, Rudsar and Lahidjan were of most developed cities and Talesh, Rezvanshahr and Amlash were the most under-developed cities respectively. After weighting indicators and according to Shannon entropy, the number of specialists and paramedics gained the most and the least weight, respectively.
Conclusion: Due to the inequality in distribution of health resources in Guilan province, attention to underdeveloped cities in this province should be a priority. To achieve equitable health resources in Guilan, it is recommended that the plannings be based on state of development of cities.