The purpose of this study was to investigate the effects of Engel coefficient, Angel coefficient and Schwabe index influencing Household head's life satisfaction. For this study, the data from the 8th analysis of the 2013 Korea Welfare Panel Survey conducted by Korea Institute for Health and Social Affairs were used. For the sample, 903 male Household heads with children under the age of 18, were selected. For statistical analysis, SPSS program (Ver. 21.0) was used. And for statistical methods, frequency and percentile, mean and standard deviation, Pearson's correlation, one way analysis of variance, Duncan's multiple range tests, multiple regression analysis were used. The findings are as follows. First, as a results of analyzing the food costs, education costs and housing costs depending on Income Quintile, the food costs and education costs in the 5th Income Quintile compared with other Income Quintile, were highest. Also, the highest housing cost was in the 2nd Income Quintile, while the least housing cost was in the 1st Income Quintile. Second, by analyzing the differences of Engel coefficient, Angel coefficient and Schwabe index according to Income Quintile, the results show that Engel coefficient and Schwabe index decreases as Income Quintile increases, and Angel coefficient increases as Income Quintile becomes higher. Third, the level of HH's life satisfaction according to Income Quintile, 1st Income Quintile, 2nd Income Quintile, 4th Income Quintile, 3rd Income Quintile, 5th Income Quintile in order, increased. Fourth, as the result of analyzing the influence of Variables related to household and demographics about Engel coefficient, Angel coefficient and Schwabe index, it was shown that the variables effecting Engel coefficient, Angel coefficient, and Schwabe index are age, occupations, Number of workers, House ownership, Income Quintile. Fifth, As a result of analyzing the Variables effecting life satisfaction, especially while Schwabe index is not that significant, Engel coefficient and Angel coefficient are shown to have a significant influence. Therefore, the influence of Food costs and education costs can be confirmed.