Iranian Journal of

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ackground & Objectives: In fact, economic growth, income inequality and health are integrated issues. Economic growth along with increasing income lead to individuals' health promotion and public health and has a positive impact on it, but if there is inappropriate policy to redistribute of these resources, it would have reverse effects. The purpose of this study was to examine the relationship between economic growth and ecological income inequality indices with health in Iran from 1978 to 2006.
Methods: An ecological study was designed and relevant data were gathered from the statistics center of Iran and Iran Central Bank. Results: The correlation between Gini coefficient and health indices was statistically significant (P<0.01). The association between economic growth and mortality rate of children under five years index (P<0.01) and with life expectancy (P<0.05) were statistically significant as well.
Conclusions: Economic development and decreasing income inequality should be considered as important determinant factors to have better health in Iranian society.

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Background & Objectives: Non-Communicable disease (NCD) is a main group of diseases which are responsible for a large proportion of the Global Burden of Disease around the world. Although disparities in the NCDs' risk factors can affect the goals of health for all, less attention has been paid so far on this topic. In this study, we investigated socio-economic inequality in the NCDs’ risk factors and evaluated the causes affecting on this inequality in Shahroud, Iran.
Methods: Conducting this survey, we used surveillance data for NCD of 1000 individuals who lived in Shahroud district during 2005. We determine a socio-economic variable which explained social and economic status of the people using Principal Component Analysis. We then evaluated each NCD risk factors at different levels of the socio-economic variable and calculated concentration index for the risk factors. The causes of the inequality were described by decomposition analysis of the concentration indices.
Results: Concentration indices for hypertension, smoking, insufficient physical activity, and unhealthy diet were -0.141, -0.191, -0.046 and -0.091, respectively. Differences of concentration curves of the risk factors from the line of equality were significant but not for diabetes, obesity and high blood cholestrol. Age, being a government employee, being unmarried, living in rural area and low economic status were the most important factors which influence on these inequalities.
Conclusion: Inequality in some NCD risk factors was significant in Shahroud district. More investigations with larger sample size and more appropriate variables to measure socioeconomic status are recommended.

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Background and Objectives: Inequity in health is a universal term which used for showing current differences, variations and inequalities of people in access to health. But inequality in health refers to some inequities which seems are unfair or caused by some errors and biases. The current study aimed to describe some of the common health related inequity measures to be useful for the inequity researchers and other interested health coworkers.
Methods: The calculation, advantage and disadvantage of most common health-inequity indexes including slope index of inequity, relative index of inequality, Theil’s Index, mean log deviation, index of disparity, Gini coefficient, weighted utilization social welfare function, absolute and relative concentration index were assessed. Inequity size of these measures was calculated by using the health care utilization survey data.
Results: Average of health care utilization in in-need subjects was 66.4%. This indicator was in the first to fifth quintiles equal to 57.6%, 63.4%, 71.6%, 69.5% and 75.3%, respectively. Relative concentration index and Gini coefficient was calculated as 0.053 and 0.0062, respectively.
Conclusion: Inequity in health care utilization in Markazi province differs based on the types of inequity measures. Selection of the inequity indexes dependent to the objective and the scale of under study variable. Among discussed indexes, concentration index determine the more accurate and also show the gradient of inequity. Therefore it can be used as the best index.

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Background and Objectives: One of the issues affecting the health sector is the presence of regional inequalities. The purpose of this study was to evaluate the trend of inequality in the distribution of human resources and health facilities in the health sector of Iran.
 
Methods: In this study, inequality in the distribution of human resources and health facilities in the health sector was assessed using the Gini coefficient in 2006, 2011, and 2015. The variables included human resources (6 indicators) and health facilities (10 indicators). Data were collected from the Statistical Center of Iran and the Statistics and Information Technology office of the Ministry of Health. For a Gini coefficient less than 0.35, 0.35-0.5, 0.5-0.6, more than 0.6 indicated relatively balanced inequality, relatively unequal inequality, high inequality, and very high inequality, respectively.
 
Results: The maximum Gini coefficient belonged to radiographic centers (0.61) and the minimum was Behvarz (0.23). In human resources indicators, inequality decreased over the study years from 0.57 to 0.27. However, inequality showed a slight increase in Behvarzes from 0.24 to 0.26. Among the facilities indicators, the Gini coefficient of urban health centers, health care facilities, beds, and radiology centers decreased from 0.45 to 0.31, whereas other indicators had an increasing trend from 0.24 to 0.59. In the private sector, there was a high inequality (0.5 to 0.61).
 
Conclusion: Eliminating inequalities in the distribution of health sector resources can help to improve justice in health outcomes. Therefore, policymakers should be pay more attention to eliminating inequalities.

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Background and Objectives: Research plays an important role in solving health problems in the community. One main mission of higher education institutions is developing research tailored to the needs of the community by providing equal and fair opportunities for research sectors. The present study aimed to measure inequality in the rea of research in Iranian medical sciences universities.
Methods: In this descriptive study, the Gini Coefficient (GC) was used to measure inequality from 2010 to 2016. The indexes included the number of published papers, citations, citation per paper, self-citation, Scimago Journal Rank (SJR), Source Normalized Impact per Paper (SNIP), Citescore, Hirsch
(h-index), number of faculty members, number of students, and educational and research budget. Stata 14 software was used for data analysis.
Results: During the study years, the GC of SJR, SNIP, and Citescore varied from 0.65 to 0.73, 0.62 to 0.73, and 0.61 to 0.72, respectively. In addition, The GC of international papers, total articles, self-citation, citation per article, Hirsch index, and total citations varied from 0.62 to 0.70, 0.56 to 0.66, 0.22 to 0.27, 0.12 to 0.28, 0.33 to 0.39, and 0.57 to 0.72, respectively. The GC of the number of faculty members and budget ranged from 0.26-0.40 and 0.34-0.67, respectively.
Conclusion: Inequality in self-citation and citation per article was relatively fair, while Hirsh and the number of faculty members had intermediate inequality. Other indicators had a high and very high inequality. To reduce inequality, developing of the balanced research infrastructures in medical universities is recommended.

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Background and Objectives: Access to equal educational opportunities is one of the fundamental rights in each country, and elimination of inequalities, especially in the higher education system, is one of the most important priorities. This study aimed to measure educational inequality in the medical sciences sector in Iranian provinces.
Methods: In this study, educational inequality in medical sciences was measured using the Gini coefficient. The study indexes included the number of students, faculty members, staff, majors and educational budget. Data were analyzed using Stata 14 software.
Results: During the study years, the Gini coefficient of the number of female students, male students, and faculty members showed a more or less decreasing trend from 0.51 to 0.46, from 0.53 to 0.46, and from 0.59 to 0.53, respectively. However, the values of inequality in the number of personnel working in educational sector and educational budget showed a slight increasing trend from 0.49 to 0.50 and from 0.53 to 0.54, respectively. According to the academic majors, the lowest Gini coefficient was related to non-continuous bachelor’s degree that varied from 0.13 to 0.17, and the highest value was related to fellowship degree ranging from 0.66 to 0.69 in the study years.    
Conclusion: Despite reduced inequality in some educational indicators, there is a high inequality in the number of academic majors of some postgraduate degrees, number of students by gender, and educational budget, which requires policy makers to focus more on balanced distribution of educational infrastructures among provinces to provide equal educational opportunities.

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Background and Objectives: Life satisfaction is one of the important dimensions of health, which is influenced by health determinants. The aim of this study was to investigate the status of socioeconomic inequalities in satisfaction with life in women aged 15-54 in Iran.
 
Methods: In this cross-sectional study, randomized multistage cluster sampling with equal clusters was done to select the participants. A total of 35,305 women aged 15-55 were enrolled in the study. Data analysis was done in two stages. In the first stage, social and economic inequalities were investigated using the concentration index and concentration curve method. In the second stage, a multilevel method was used to identify the determinants.
 
Results: The mean life satisfaction was 12.81±4.23. The concentration index for dissatisfaction with life was -0.06 [95% CI: -0.1, -0.02], indicating dissatisfaction with life in low socioeconomic groups. The results of multilevel analysis showed that age, marital status, occupation, place of living, education, and the economic class correlated with dissatisfaction with life in women (P<0.05).
 
Conclusion: There is inequality in dissatisfaction with life. Dissatisfaction is concentrated in the poorer groups of the society and varies in different provinces. Socioeconomic variables affect inequality in satisfaction with life in women, which need to be addressed to reduce inequalities.

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Background and Objectives: This research was conducted to investigate the socioeconomic and geographical inequality in mortality from road traffic accidents in Iran in 2016.
 
Methods: In this descriptive cross-sectional study, the data of 16,584 people that died from road traffic accidents in 2016 were received from the Legal Medicine Organization. Theil entropy index was used to determine inequality in geographic areas. Moreover, relative and absolute concentration indices were used to measure inequality in mortality from RTAs across educational levels.
 
Results: The mortality rate from road traffic accident was 21.5 per 100,000 people. Theil index was 0.66 for traffic-related deaths among the provinces, indicating an unequal distribution of traffic injuries caused by traffic accidents among the provinces. When inequality was measured at smaller geographical levels, i.e., among cities in each province, the results indicated a fair distribution across smaller geographic levels. The focus index also indicated a fair distribution of traffic accidents among the deceased sub-classes (concentration index & 95% CI: -0.13 (-0.41; 0.16).
 
Conclusion: Our findings showed that the distribution of mortality from road traffic accidents was unequal at provincial positions. According to our findings, mortality from traffic accidents was distributed equally among the socioeconomic and urban levels. Therefore, health managers can use the findings of this study to develop interventions to reduce inequalities. In addition to targeting factors contributing to known social inequalities in the health and social status, other factors should be considered and applied to evaluate their interventions in the future.

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Background and Objectives: The main purpose of this study was to compare the predictive power of the Inequality-adjusted Human Development Index (IHDI) with the Human Development Index (HDI) with regard to the share of deaths caused by Non-Communicable Diseases (NCD) among all deaths in the world and Iran.
 
Methods: The data required for this cross-sectional ecological study were extracted from the reports of the United Nations Human Development Program and the WHO in 2015. Pearson correlation test was used to investigate the correlation of HDI and IHDI with the share of deaths caused by NCDs and linear regressions models were used to determine the associations of IHDI and HDI with the dependent variable.
 
Results: At a significant level of P<0.01, the dependent variable showed a strong positive correlation with HDI (0.892) and IHDI (0.899). Simple linear regression showed that HDI alone predicted the dependent variable well (Adj.R2=0.794, P<0.001).However, according to the multivariate linear regression model, when IHDI and HDI were included in the model, IHDI was able to predict the dependent variable well (Adj.R2=0.809, P=0.001), while the relationship between HDI and the dependent variable was no longer significant.
 
Conclusion: Although HDI alone is an important predictor of NCD status, it loses its influence in the presence of IHDI. Therefore, in addition to HDI, IHDI that illustrates the impact of inequality on human development can provide more information on the status of deaths caused by NCDs.
 

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Background and Objectives: Fair financial protection against health expenditures is one of the most critical goals of health systems. This study was conducted to investigate the most appropriate threshold for measuring the exposure to catastrophic health expenditure (CHE) in Iran.
 
Methods: The present study was conducted using 2018 national household income and expenditure data of the Iran statistics center. The occurrence and intensity of the households' exposure to CHE at different thresholds and for economic quintiles was measured using two World Health Organization (WHO) and World Bank (WB) methodologies. The most appropriate threshold for each methodology was also determined using the Kappa statistics adaptation estimation.
 
Results: The occurrence of households’ exposure to CHE was 3.02% and 8.51% in urban households and 4.66% and 9.22% in rural households, respectively. According to asset quintiles, the highest occurrence was in the first quintile and the lowest in the fifth quintile. In addition, the results of adaptation estimation based on Kappa statistics showed that a threshold of 40% in the WHO methodology and 25% in the WB methodology were the most appropriate thresholds.
 
Conclusion: The results showed a relatively high rate of exposure to CHE. CHE occurrence was also more in poorer households, and common thresholds were the most appropriate thresholds for estimating CHE.