ABSTRACT
Background: The demand for cosmetic surgery is on the rise worldwide, making it the common form of surgery globally while the use of cosmetic surgery being exponentially high in Iran. The aim of this study was to investigate inequality in the use of cosmetic services and surgery (CSS) among Iranian households concerning demographic and socio-economic characteristics. Methods: This study used data of 38960 Iranian household from the income-expenditure survey of the statistical center of Iran (SCI) in 2019. Concentration index (C) was used to measure inequalities in the use of CSS. Microsoft Excel sheet 2019 was used to extract the data, and the analysis was performed using Stata statistical package version 14.2. Results: Households with female head, with single head, households with 3 - 4 people, headed with undergraduate education person, households with insurance coverage, with higher socio-economic quintiles, rural households and residents of northwestern Iran were accounted for the highest use of CSS. Also, according to the decomposition analysis, wealth and education level are the two main factors in creating inequality, with wealth, having the highest positive share (88.11%) and education level having the most negative share (-5.26%) in creating measured inequality. Conclusion: The use of CSS is more concentrated in well-off households in Iran. As the resources of health system are limited, the government and the policy makers should have defined plans with regards to CSS use especially taking factors like socioeconomic status and education status of target groups in to account.
ABSTRACT
BACKGROUND: One of the important aspects of equity in health is equality in the distribution of resources in this sector. The present study aimed to assess the distribution of hospital beds in Shiraz in 2014. METHODS: In this retrospective cross-sectional study, the population density index and fair distribution of beds were analyzed by Lorenz curve and Gini coefficient, respectively. Descriptive data were analyzed using Excel software. We used Distributive Analysis Stata Package (DASP) in STATA software, version 12, for computing Gini coefficient and drawing Lorenz curve. RESULTS: The Gini coefficient was 0.68 in the population. Besides, Gini coefficient of hospital beds' distribution based on population density was 0.70, which represented inequality in the distribution of hospital bedsamong the nine regions of Shiraz. CONCLUSION: Although the total number of hospital beds was reasonable in Shiraz, distribution of these resources was not fair, and inequality was observed in their distribution among the nine regions of Shiraz.
