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Household health expenses (HHE) are an important problem in any area. This national study aimed to investigate the determinants of HHE using quantile regression methodology. This cross-sectional national survey data was collected through the Iranian households’ income and expenditure survey, administered by the Statistical Centre of Iran (SCI) in 2014. In total, 38299 households were selected by a three-stage stratified cluster sampling method. The data were collected using a standard SCI-made Household Income and Expenditure questionnaire. A quantile regression (QR) approach was employed to determine the key predictor variables of HHE. R programming language (ver. 3.3.0) was used for data analysis. The findings indicated that the median annual medical expenses per capita was 1020000 Rls (= 48.02 USD) for Iranian households. The results of QR modeling revealed that age, income, region, gender, literacy, and occupational status had significant effect on HHE. Among households with moderate HHE, families with older-female-higher income heads experienced more HHE, while among high HHE households, families with older-rural-higher income heads spent more on HHE. Since inequality at HHE was revealed by age, income, region, gender, literacy, and occupational status among Iranian households, more attention will be needed from policymakers and health sectors on population subgroups of Iran.

Keywords: Health expenses, Household, Quantile regression

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