Assessing the quality of life among Pakistani general population and their associated factors by using the World Health Organization's quality of life instrument (WHOQOL-BREF): a population based cross-sectional study.

ABSTRACT

BACKGROUND: Measuring quality of life (QOL) in a population is important for the predictions of health and social care needs. In Pakistan, health related quality of life data exist but there are no quality of life data of general population. In this study, quality of life was assessed among the Pakistani general population and their associated factors by using the World Health Organization's quality of life instrument (WHOQOL-BREF). METHODOLOGY: A population-based cross-sectional study was carried out in all 52 Union Councils of District Abbottabad, Khaber Pkutunkhua province, Pakistan from March 2015 to August 2015. Multi-stage cluster sampling technique was employed in this study. Quality of life was measured by using the validated WHOQOL-BREF instrument, along with socioeconomic, demographic, and World Bank social capital questions in this population- based study. The data were collected through households, utilizing face to face interviews. The association between socio-demographic variables and quality of life domains were determined by using both univariate and multivariate analysis. Descriptive statistics were derived, and a multilevel linear regression using backward analysis allowing to obtain final model for each domain was achieved to recognize the variables that affect quality of life score. RESULTS: A total of 2063 participants were included in this study (51.2% male, 48.2% female). Mean age of participants was 37.9, SD = 13.2; ranging from 18 to 90. Mean score of quality of life domains (physical, psychological, social relationship and environmental domains) were 65.0 (SD = 15.2), 67.4 (SD = 15.0), 72.0 (SD = 16.5), 55.5 (SD = 15.0), respectively. Overall, socioeconomic status was established to be the strongest predictor of poorer quality of life for all domains as a change in SES from high to low results in reduction about (ß = - 5.85, ß = - 9.03, ß = - 8.33, ß = - 9.98, p < 0.001). Similarly, type of residency was negatively associated with physical, psychological and environmental domains while age and sex were negatively associated with physical, psychological and relationship domains in final model. Furthermore social capital (ß = 0.09, ß = 0.13, ß =0.14, ß =0.15, p < 0.001) had a positive effect on Pakistani quality of life. Overall, subjective quality of life was found to be low in our population and extremely varied by socio-demographic variables. CONCLUSIONS: Increasing age, having average and lower socioeconomic status and living in the rural area were found to be the strong predictor of poorer quality of life in all domains, while total social capital score had a positive effect on Pakistani quality of life scores.