Objectives: Economic development, income inequality and health issues have integration. The relationship between population health, inequality in income, distribution and economic growth has attracted much attention during the last two decades. In other word, economic development, economic growth and income inequality as socioeconomic parameters or social determinants health (SDH) are effective for supply and promotion of health. In resent decade’s whit transformation in illnesses epidemiology from infectious diseases to chronic diseases, attention to social environmental and mental causes increased instead of clinical causes. The objectives purpose of this paper is to examine that relationship and regression analysis between income inequality, economic development and economic growth index with health index using Iran time- series data. We analysis included 31years, 1355-1385. Method: In this study used of correlation and regression analyses. For the selected years, Predictor’s variables are economic development, economic growth and income inequality. And dependent variables are life expectancy at berth and under 5year children mortality rate. In this study we used of economic growth as control variable. Necessary data and information for study correlated from the central bank and statistical center of han. For preparing the data used of EXCEL software, first we collected primitive and fresh data then interred theme EXCEL software to gain necessary data. The analysis of correlated data was done with the help of SPSS software. h) Findings: the propos of present study is analysis relationships between study variables. Gini coefficient has significant coloration (p<.001) with life expectancy (R=-0.73, P=0.000) also with under 5 years children mortality rat(R=0.77, P=0.000). And economic development has significant coloration (p<.05) with life expectancy (R=0.38, P=0.03) also with under 5year children mortality rat (R=-0.4, P=.0027). After used of partial coloration economic growth shown significant coloration (in p<0.01signification level). When regression analyses was don, observed that income inequality is stronger predictor to variance health variables (P=0.75, p=0.79). Results: the important difference of this study is to various indexes. This character helps to have deeper knowledge about variables. Decreasing of income inequality and increase economic development will cause of increase in health indexes (increase in life expectancy and decrease in fewer than 5year children mortality rat). According to data income inequality trend is decreasing and economic growth and economic development trends are variable. But health status trend is increasing. Although decreasing in economic growth on 1356‌1368, health indices were promoted. Because, during in this years, Islamic revolution governments whit society approach adopted social policies such as universal education, health care social security ,and social services such as subsides that resulting to increase in income inequality. By attention to findings of regression analyses, before that economic growth interred to model, income inequality was stronger variable than economic development (P=0.75, p=0.79). But with existed economic growth, economic development was strongest variable. Generally, seem for health promotion, we must be attention to both economic development and income redistribution issues.

Introduction: The modern concept of distributive justice focuses on equitable distribution of resources and advantages in society. Besides, health as one of the social welfare sub-category is under affects of distributive justice indicators. In this study, the relationship between health and distributive justice indicators, from 1984 to 2006, has been studied.

  Method: This study is an ecological analysis. For measuring distributive justice as independent variable, income inequality, and poverty and government expenditures indicators were used and for measuring health, life expectancy and infant mortality rates were used. At the first, the data gathered from national statistic center and then by using Stata and Excel soft ware, indicators derived, and finally the associations between indicators by using SPSS software was analyzed.

  Findings: In this period the trend of poverty and income inequality indicators were declining and health indicators were rising. Correlation analysis indicated that there is relationship between distributive justice indicators and health indicators but by controlling government expenditures in partial correlation, there is no relationship between mentioned indicators. With using of bivariate regression, poverty was more explanatory than income inequality. Meanwhile, this fact revealed that government expenditures in health have most explanatory among distributive justice indicators.

  Conclusion: Taking account results of study, distributive justice indicators have a significant relationship with health indicators and in this period with increasing distributive justice indicators, health indicators have improved. Also, among the studied distributive justice indicators, government expenditures in health have the most relationship and explanatory power. So, it seems that government investment in health sector for obtaining distributive justice goal and promoting of health is necessary.