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Showing 3 results for Ghaderi
The Relationship Between Macroeconomic Variables And Health Indicators In United Nations Member States: 2002-2010
Mehdi Khakian, Javad Neshani Sadabad, Mohammad Hadian, Hosein Ghaderi, Malihe Ram, Yaser Jouyani,
Volume 9, Issue 4 (11-2015)
Abstract

Background and Aim: In a severely inflationary environment with unemployment, social problems increase and, therefore, high health care expenses are imposed on the society.

Materials and Methods: This was a correlational study. Panel data model and EVeiws 6 software were used in this study. The data were collected from the World Bank website. The required pre-tests, including F-Limer and Hauseman tests, were given to check the appropriateness of data and to determine a appropriate model. Following the pre-tests, the results were estimated in the form of a regression model.

Results: The results indicated that F-test and t-statistic were significant, and that R2 statistic was high. In the three models, R2 was 99%, 99% and 98%, respectively. Moreover, it can be said that employment is positively related with life expectancy, but negatively related with infant mortality and total fertility rate. Also, inflation is negatively related with life expectancy, but positively related with infant mortality, and total fertility rate. Finally, Gross Domestic Product (GDP) is negatively related with total fertility rate and life expectancy, but has no meaningful relationship with infant mortality (p = 0.31).

Conclusion: Employment, inflation and GDP are the variables that have the greatest impact on health indicators. however, life expectancy is more sensitive to explanatory variables.


The Effect of Socioeconomic Factors on Household Health Expenditures: Heckman Two-Step Method
Mahdi Shahraki, Simin Ghaderi,
Volume 13, Issue 2 (Jun & Jul 2019)
Abstract
Background and Aim: Due to the high level of out-of-pocket payments for health expenditures and the importance of household health expenditure management, this study aimed to investigate socioeconomic factors affecting Iranian urban households’ health expenditures.
Materials and Methods: This descriptive-analytic and applied study was conducted cross-sectionally at national level with microeconomic approach. The sample included 18809 urban households living in Iran's provinces in 2016; they were selected by three-stage sampling method. Data were collected by the household income-expenditure questionnaire of Statistical Center of Iran (SCI). The results were evaluated in Stata 14 software using Heckman two-step method.
Results: The results showed that socioeconomic factors such as increasing of income and insurance expenditures, having insurance, number of employed people, head's literacy, increasing of per capita expenditures of tobacco and education led to an increase in household health expenditures. Mother-headed households had lower health expenditures than others; and head of household’s age, household size, and the presence of elderly persons led to an increase in household health expenditures.
Conclusion: Household socio-economic factors not only affected the decision to enter health market but also influenced the purchase of goods and health services and inequality in health sector. Therefore, certain policies are essential to improve the socio-economic status towards reducing inequality in health sector; such a thing can be achieved through employment creation, growth of income, investment in education, and increase of insurance coverage.

Forecasting of Physicians Supply and Demand in Medical Sciences Universities of Iran
Mahdi Shahraki, Simin Ghaderi,
Volume 14, Issue 4 (Oct & Nov 2020)
Abstract
Background & Aim: Physicians as human capital and resources are one of the main components of health production. The imbalance of physician supply and demand affects the health and economics. Therefore, this study aimed to estimate and forecast the supply and demand of physician working in Iranian medical universities.
Materials and Methods: This a descriptive-analytical and applied study was conducted at national level for Iran during 1991-2017. The statistical population was physicians working in Iranian medical universities. ARIMA method was used to estimate and forecast physician supply and Vector Error Correction Models was used for physician demand. The data is annual time series that was extracted from the statistical yearbooks of the Statistical Center of Iran and the World Bank database. Eviews 10 software was used to estimate the models.
Results: The results showed that physician demand in Iran was affected by Gross Domestic Product, age structure and hospital beds, and according to the forecast of supply and demand of physicians, we will be faced to the physician shortage in the years 2018-2030.
Conclusion: In the coming years, Iran is facing with physician shortage. Therefore, it is recommended to adopt policies to increase physician capacity in medical universities and to increase strong incentives to retain physicians and prevent their migration.

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