Quality of life of childbearing age women and its associated factors: an application of seemingly unrelated regression (SUR) models

Purpose

This article is a report of using seemingly unrelated regression (SUR) models to examine the determinants of different dimensions of quality of life (QoL) among childbearing age women. There are a limited number of studies on QoL and its associated factors among women in developing countries such as Iran. Therefore, more attention should be focused on identifying these issues.

Methods

We administered the Persian’s abbreviated version of the World Health Organization Quality of Life (WHOQOL-BREF) questionnaire to 1,067 married women aged between 15 and 49 years. The women were chosen via a multistage research design from the rural region of Shiraz, the center of Fars Province in Iran in 2008. Clinical and socio-demographic characteristics as well as their reproductive health-related characteristics were investigated. To identify associated factors of QoL dimensions, ordinary least squares (OLS) regression and SUR were used and their findings were compared.

Results

The WHOQOL-BREF showed acceptable consistency (Cronbach’s alpha range: 0.62–0.75 across domains). Lower age, absence of long-term illness, economic status satisfaction, higher level of education, lower number of pregnancies, and higher body mass index were important associated factors of different dimensions of the QoL among these women. The estimated parameters for these factors were in close agreement in both OLS and SUR estimation methods. However, the SUR estimator provided the higher precision of the estimates than the OLS estimator, as the parameters obtained by SUR are characterized by lower standard errors. Women’s age, income satisfaction, and level of education were common for all domains.

Conclusions

This study presents a novel approach to simultaneously predict QoL domains using the SUR estimators and the results are relevant for implementing objective QoL. SUR estimators performed consistently better than the OLS estimators, since SUR takes the correlation between error terms into account. Thus, the SUR method could be a useful methodology for predicting QoL domains.