Iranian Journal of

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  Background & Objectives : In recent years, the World Health Organization has paid more attention to the relationship between health and social conditions as determining the factors affecting people's health in the society. Social health factors (conditions in which people are born, grow up, work, and become old, and also the health system available for them) have caused inequalities in health and require more attention in health development. The purpose of this research was to identify the determining social and economic factors which are effective in mortality in these selected countries during 1998-2009.

  Methods: Countries were divided into 3 groups based on the human development index and 10 countries out of each group were studied randomly. The dependent variable in this research was overall mortality and the explanatory variables were Gini coefficient, unemployment rate, per capita Health expenditure, and also the result of multiplication of per capita income and Gini coefficient. To evaluate and assess the data, the generalized method of moment by Eviews 6 was used.

 Results: The findings showed that the most determining elements affecting the mortality rate in countries with a very high human development index were Gini coefficient (0.02), unemployment rate (0.0001), and the variable obtained by multiplying the Gini coefficient by per capita income (-8.1*10-6). In countries with a high human development index, the most determining elements affecting the mortality rate were unemployment rate (0.005), per capita expenditure (-0.0002), and the variable obtained by multiplying Gini coefficient by per capita income (-3.22*10-6). Also, in countries with a medium human development index, the most determining elements affecting the mortality rate were per capita expenditure (-0.0008), and multiplication of Gini coefficient and per capita income (1.47*10-6).

  Conclusion: It can be concluded that based on the level of development of the countries, various economic and social factors can affect the mortality and health level of those countries. Therefore, it is necessary for the countries to plan for their health system if they wish to eradicate or reduce inequalities and injustices. This plan should be based on their level of development, the factors determining mortality, and the health system of those countries.

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Background and Objectives: Burns are tragic events with considerable mortality rates. This study was conducted to analyze the spatial pattern of burns and identify the factors associated with the burn injuries in Mashhad, Iran.
 
Methods: This retrospective cross-sectional study was conducted in patients hospitalized in Imam Reza Hospital Burn Center, Mashhad, which is the only referral burn center in the northeast of Iran. Spatial generalized linear models (Poisson and negative binomial) were used to model the association between socio-economic characteristics and the incidence of burn injury.
 
Results: A total of 1044 acute burn patients (69.9% male, 30.1% female) were reviewed. Most of the burned patients were in the age group 20-29 years (41.4%). The most common cause of burn injury was flame (64.6%). The local test of spatial autocorrelation confirmed that the burns had cluster pattern in the central areas of the city and the worn-out urban texture was at higher risk of burns. The results of model showed that the percentage of worn-out urban texture (IRR =1.007; 95%CI 1.005-1.008), literacy (IRR =0.98; 95% CI 0.95-0.99), percentage of employed women (IRR =0.96; 95%CI 0.92-0.99), unemployment rate (IRR =0.92; 95%CI 0.85-0.99) and percentage of margination (IRR =1.006; 95%CI 1.005-1.008) were associated with burns.
 
Conclusion: Based on the findings, socio-economic and environmental characteristics are associated with the incidence of burn injuries in different areas. The results of this study could be used to design burn prevention strategies, especially in the high-risk areas and groups.

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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: The Covid-19 epidemic began in Wuhan, China in the late 2019 and became a global epidemic in March 2020. In this regard, one of the most important indicators of the healthcare systems is the in-hospital mortality rate, which occurs with a time lag of one to two weeks after hospitalization. The aim of this study was to investigate the relative risk of Covid-19 mortality considering this time lag according to the number of daily hospitalizations.
 
Methods: The data included the number of daily hospitalizations and deaths from Covid-19 from 15 May 2020 to 10 February 2021 in Iran, which was obtained from the Github database. A log-linear distributed lag model was used to evaluate the relationship and lag effect between daily hospitalization and relative risk of death.
 
Results: The mean number of daily hospitalizations and deaths were 1342.2 ± 7 731.5 and 190.6 11±118.6 in the study period, respectively. It was found that an increase in the number of daily hospitalizations had a significant relationship with an increase in the relative risk of death on the same day and in the following days. As the number of hospitalizations exceeded 2000 patients per day, the cumulative relative risk of death increased to more than one.
 
Conclusion: The results showed that the number of hospitalizations exceeding 2000 people per day was an alert for the country's healthcare system. Overall, prevention and observance of health protocols in the first level followed by early diagnosis of the disease, improving the hospitals facilities and preparedness of healthcare staff can reduce the relative risk of death in the possible future peaks.