A key challenge for equality evaluation and monitoring, mainly in developing countries, is assessing socioeconomic status (SES) of individuals. This difficulty along with low technical competency, have resulted in many health information collected in these countries which are devoid of suitable SES indices. However, simplifying data collection requirements for estimating economic parameters seems to guarantee their wide adoption by survey and health information system (HIS) designers, resulting in immediate production of equity-oriented policy-relevant information. The goal of this study is obtaining adequate number of variables, which their combination can provide a valid assessment of SES in Iranian population.
The data source was Living Standards Measurement Study of Iran (2006). Data of 27,000 households on the ownership of 33 household assets was used for this analysis. Households of this study were divided into 5 groups in terms of SES status using principle component analysis. Then selection was made among the 33 variables so that a combination with minimum necessary number for obtaining SES status is reached. Agreement of the new combination (including minimum number of variables) with full variable combination (including all 33 variables) was assessed using weighted kappa.
A minimum set of six variables including having kitchen, bathroom, vacuum cleaner, washing machine, freezer and personal computer could successfully discriminate SES of the population. Comparing this 6 item-index with the whole 33 item-index revealed that 65% of households were in the same quintiles, with a weighted kappa statistics of 0.76. For households in different quintiles, movement was generally limited to one quintile, with just 2% of households moving two or more quintiles.
The proposed simple index is completely applicable in current Iran's society. It can be used in different survey and studies. The development is quite simple and can be done on a yearly basis using the updated National level data. Having such standardized simplified and up to date SES indices and incorporating them into all health data sources can potentially ease the measurement and monitoring of equity of health services and indices.