BackgroundMeasuring 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).MethodologyA 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.ResultsA 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 (β = − 5.85, β = − 9.03, β = − 8.33, β = − 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 (β = 0.09, β = 0.13, β =0.14, β =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.ConclusionsIncreasing 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.Electronic supplementary materialThe online version of this article (10.1186/s12955-018-1065-x) contains supplementary material, which is available to authorized users.

Background and Objectives: In order to curb the spread of coronavirus disease 2019 (COVID-19), the countries took preventive measures such as lockdown and restrictions of movements. This can lead to effects on mental health of the population. We studied the impact of COVID-19 on psychological well-being and associated factors among the Pakistani general population.Methods: An online cross-sectional survey was conducted between 26th April and 15th May and included participants from all over the Pakistan. Attitudes and worriedness about COVID-19 pandemic were assessed using a structured questionnaire. A validated English and Urdu version of the World Health Organization Well-Being Index (WHO-5) was used to assess the well-being. Factor analysis was done to extract the attitude item domains. Logistic regression was used to assess the factors associated with poor well-being.Results: A total of 1,756 people participated in the survey. Almost half 50% of the participants were male, and a similar proportion was employed. About 41% of the participants were dependent on financial sources other than salary. News was considered a source of fear as 72% assumed that avoiding such news may reduce the fear. About 68% of the population was worried about contracting the disease. The most common coping strategies used during lockdown were spending quality time with family, eating healthy food, adequate sleep, and talking to friends on phone. Prevalence of poor well-being was found to be 41.2%. Female gender, being unemployed, living in Sindh and Islamabad Capital Territory (ICT), fear of COVID-19, and having chronic illness were significantly associated with poor well-being. Similarly, coping strategies during lockdown (doing exercise; spending time with family; eating healthy food; having good sleep; contributing in social welfare work and spending time on hobbies) were also significantly associated with mental well-being.Conclusion: We found a high prevalence 41.2% of poor well-being among the Pakistani general population. We also investigated risk factors of poor well-being which included female gender, unemployment, being resident of ICT and Sindh, fear, chronic illness, and absence of coping strategies. This calls for immediate action at population level in the form of targeted mass psychological support programs to improve the mental health of population during the COVID-19 crises.

Background Advantages and disadvantages associated with joint and nuclear family systems can affect quality of life (QOL). However, there is scarcity of literature about QOL among joint and nuclear family systems. This study aimed to assess the factors associated with QOL in joint and nuclear family systems. Methods We conducted a population based cross sectional study in all 52 Union Councils (UCs) of District Abbottabad, Khyber Pakhtunkhwa province, Pakistan from March 2015 to August 2015. Multistage cluster sampling technique was used to select participants from both nuclear and joint family houses. The validated Urdu version of World Health Organization Quality of Life Questionnaire-Brief Version (WHOQOL-BREF) was used to assess quality of life among participants. Univariate and multivariate analyses were performed to explore the associations of different socio demographic variables with QOL among both family systems. Also a multilevel linear regression using backward analysis to obtain final model for each domain was performed to find out the variables that are associated with QOL score in each of family systems. Results A total of 2063 participants were included in this study (51.0% joint family, 49.0% nuclear family) with the response rate of 97.4%. In multiple linear regression analysis of each domain for joint and nuclear family systems, rural residence compared to urban (p < 0.001), being female (p < 0.001), older age (p < 0.001), having comorbidity (p < 0.001) and lower socioeconomic status (p < 0.001) were found to be a strong predictor of poorer QOL. Furthermore, social capital (p < 0.001) had a positive effect on joint and nuclear family QOL scores. Conclusion This study was the first of its kind which determined the factors of QOL in joint and nuclear families using the validated Urdu version of WHOQOL-BREF in Pakistan. Male gender, urban residence, younger age, higher socioeconomic status and social capital were positive predictors of QOL score while older age and presence of illness were associated with lower QOL scores among both family systems.