Last update:
16-Sep-2004

OBJECTIVE The objective of our study was to measure quality of the Hungarian general population and to identify the relationship between key socio-economic variables and quality of life (QoL).

METHOD Surveys including the EQ-5D instrument and other questions about socio-economic status were conducted on representative samples of adults at 2 typical cities in Hungary and 3 typical districts of the capital of Hungary in 1996. Data were pooled from the five data sets. The overall sample size was 4,083. Mean QoL values were calculated in various socio-economic groups. Differences in quality-adjusted life expectancy were calculated by combining life expectancy data of the Central Statistical Office and QoL values from the current data set. The Le Grand method was used to measure inequity in the delivery of health care. This index was based on levels of concentration of physician visits and concentration of ill health in different income groups. Ill health was defined as 1-the EQ-5D index.

RESULTS Main risk factors for having lower QoL were age, low income, being divorced or widow, having low education, and being female. People between the age of 15 and 24 had a mean EQ-5D index of 0.97 compared to people over 85 with a mean value of 0.50. Mean QoL values in the four income groups were 0.73, 0.84, 0.95, 0.93, respectively. Income had surprisingly strong influence on QoL within each age group. People who were divorced or widows had lower QoL than people being single or married, 0.72 versus 0.86 respectively. People with low or lower-middle education level had lower QoL compared to people with high or higher-middle education level, 0.76 versus 0.87 respectively. Apart from the youngest age group, women had consistently lower QoL values than men. Overall mean values were 0.86 versus 0.79 respectively. Due to a larger difference in life expectancy (74.7 versus 66.1 years), quality adjusted life expectancy results still favoured women. The difference, however, got smaller, 64.2 versus 60.6 quality adjusted life expectancy. Data indicates that the level of concentration of ill health among the poor is higher than the concentration of health care consumption. Small but positive value of the Le Grand index of 0.06455 indicates a system that slightly favours the rich.

CONCLUSIONS Our results showed that substantial socio-economic differences exist in quality of life within the Hungarian population. Data implied that health promotion should focus on lengthening life in the case of men while it should focus on improving quality of life in the case of women. Reduction in inequalities in health status can not be achieved without tackling income inequalities.

Key words: EQ-5D, Health inequalities, Hungary, Illness concentration, Le Grand method.