Factors and Predictors of Health Related Quality of Life of the General Population of Pakistan

Background and ObjectiveThe standards of living, improvement in public health, and medical care in Pakistan are increasing day by day, health-related quality of life (HRQoL) has been increasingly acknowledged in various patient's reported outcomes in Pakistan. However, a large-scale general population-based study on assessing HQRoL in Pakistan was not conducted. Therefore, this study aimed to evaluate HRQoL for the general Pakistani population. Material and MethodsA cross-sectional study with a population sample (n = 16,672) was selected from all Pakistan provinces using a stratified sampling approach. The EQ-5D-3L tool was used to measure the HRQoL of the general population of Pakistan. The descriptive and inferential statistics have been done by using SPSS version 20. ResultsOverall, 121 health states were reported in this study. EQ-5D index and EQ-VAS scores were 0.74 +/- 0.32 and 0.75 +/- 0.25, respectively. The percentage of people responding to any problems increased with age. Males have better health as compared to females in all age groups. All demographics were significantly associated (P < 0.01) with the mean EQ5D index and VAS scores except residence (p > 0.05). The regression model reported that age was the best predictor of the EQ-5D index scores after adjusting for the covariates (beta = 0.19; p < 0.001). This study provides Pakistani population HRQoL data measured by the EQ-5D tool, based on a national representative sample. ConclusionThe current study concluded that Age, City, Gender, Education, Occupation, Residence, and House occupancy are significantly affecting HRQOL. The socioeconomically deprived groups and females have inferior health status than more advantaged. The trends detected in high-income nations were usually similar to Pakistan.

Automated summary

This study aimed to evaluate the health-related quality of life (HRQoL) for the general population of Pakistan. The results showed that age, city, gender, education, occupation, residence, and house occupancy significantly affected HRQOL. Socioeconomically deprived groups and females had inferior health status compared to more advantaged groups. Similar trends were observed compared to high-income nations.