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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

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 Paki...

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Autores principales: Lodhi, Fahad Saqib, Montazeri, Ali, Nedjat, Saharnaz, Mahmoodi, Mahmoud, Farooq, Umer, Yaseri, Mehdi, Kasaeian, Amir, Holakouie-Naieni, Kourosh
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6332637/
https://www.ncbi.nlm.nih.gov/pubmed/30642360
http://dx.doi.org/10.1186/s12955-018-1065-x
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author Lodhi, Fahad Saqib
Montazeri, Ali
Nedjat, Saharnaz
Mahmoodi, Mahmoud
Farooq, Umer
Yaseri, Mehdi
Kasaeian, Amir
Holakouie-Naieni, Kourosh
author_facet Lodhi, Fahad Saqib
Montazeri, Ali
Nedjat, Saharnaz
Mahmoodi, Mahmoud
Farooq, Umer
Yaseri, Mehdi
Kasaeian, Amir
Holakouie-Naieni, Kourosh
author_sort Lodhi, Fahad Saqib
collection PubMed
description 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 (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. 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12955-018-1065-x) contains supplementary material, which is available to authorized users.
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spelling pubmed-63326372019-01-16 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 Lodhi, Fahad Saqib Montazeri, Ali Nedjat, Saharnaz Mahmoodi, Mahmoud Farooq, Umer Yaseri, Mehdi Kasaeian, Amir Holakouie-Naieni, Kourosh Health Qual Life Outcomes Research 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 (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. 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12955-018-1065-x) contains supplementary material, which is available to authorized users. BioMed Central 2019-01-14 /pmc/articles/PMC6332637/ /pubmed/30642360 http://dx.doi.org/10.1186/s12955-018-1065-x Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Lodhi, Fahad Saqib
Montazeri, Ali
Nedjat, Saharnaz
Mahmoodi, Mahmoud
Farooq, Umer
Yaseri, Mehdi
Kasaeian, Amir
Holakouie-Naieni, Kourosh
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
title 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
title_full 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
title_fullStr 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
title_full_unstemmed 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
title_short 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
title_sort 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
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6332637/
https://www.ncbi.nlm.nih.gov/pubmed/30642360
http://dx.doi.org/10.1186/s12955-018-1065-x
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