Investigating predictors of health-related quality of life and functional status in middle-aged to older adults with hypertension in a selected urban community

dc.contributor.advisorPuoane, Thandi
dc.contributor.authorClayford, Mario
dc.date.accessioned2020-03-27T10:18:07Z
dc.date.accessioned2024-11-07T09:37:11Z
dc.date.available2024-11-07T09:37:11Z
dc.date.issued2020
dc.descriptionPhilosophiae Doctor - PhDen_US
dc.description.abstractIntroduction: In this study, predictors of health-related quality of life and functional status in people with hypertension were investigated. Hypertension is the leading preventable cause of premature death. Aims: The aims of the study were to (1) assess the relationships between socio-demographic variables, psychosocial variables and disease morbidity with health-related quality of life (HRQoL) and functional status (FS) outcome variables, and (2) develop multivariate predictive models to predict H-RQoL (social, psychological, physical and environmental) and FS physical component summary (PCS) and mental component summary (MCS) outcomes. Methods: A sample of 173 hypertensive participants was subjected to self-administered questionnaires to assess their levels of H-RQoL and FS. Secondary data, including anthropometric and blood pressure measurements, disability and chronic disease were used from the South African Prospective Urban Rural Epidemiology Study, University of the Western Cape. Additional data were collected using a series of questionnaires, 1.) a personal and demographic questionnaire, 2.) the World Health Organization Quality of Life – Brief, the Medical Outcomes Survey Short-Form 36 version 2 (SF 36 v2), and 3.) the Proactive Coping Inventory (PCI) questionnaire. Using systematic data analysis, we assessed (1) relationships between socio-demographic, psychosocial and disease morbidity variables through correlational analysis (Pearson r, ANOVA), and (2) the value of socio-demographic, psychosocial and disease morbidity variables in predicting H-RQoL and FS through multivariate regression analysis yielding six separate regression models. Results: Findings revealed demographic factors (education, marital status), psychosocial factors (coping, stress) and disability were significant predictors of H-RQoL and FS. Marital status, home, work, and financial stress was significantly associated with improved physical, social relationships and environmental quality of life. Engaging in reflective, strategic, preventive, instrumental, emotional and avoidance coping had a significant and positive effect on physical quality of life, but had significant negative effects on social relationships (and environmental quality of life. Having several disabilities negatively affected the quality of life across all subscales. For FS, the PCS was significantly associated with age, marital status and employment, and negatively with strategic, emotional support seeking and avoidance coping. Financial stress, stress at home, and religious group involvement were significantly associated with the MCS. Predictors in the psychological QoL model explained 28% of the variance in the model. Having secondary schooling (p=0.002) and some stress at home (p=0.001) significantly predicted the psychological quality of life. Not belonging to a religious group (p=0.019) had a positive influence on social relationships QoL and having moderate financial stress (p=0.028) had a negative impact, explaining 27% of the variance in the model. Having a college or university education (p=0.039) and utilising reflective coping (p=0.006) predicted increased physical QoL significantly, whereas strategic coping predicted decreased physical QoL. Predictors in the physical QoL model explained 23% of the variance in the model. Possessing a college or university education (p=0.009) and being unemployed because of illness or old age (p=0.029) significantly predicted increased environmental QoL. Having several limitations (p=0.002) resulted in five times lower environmental QoL. The predictors in the model could explain only 19% of the variance in the model. The final model for the PCS revealed reflective coping (p=0.042) was the only predictor that increased physical FS. Being currently married (p=0.001), divorced or separated (p=0.013), having secondary schooling (p=0.003) or college or university education (p=0.004), engaging in avoidance coping (p=0.043) and having several disabilities (p=0.000) significantly decreased physical FS, explaining 40% of the variance in the model. In the MCS final model, emotional coping (p=0.053) increased mental FS. Being currently married (p=0.011), divorced or separated (p=0.006), having stopped working because of illness (p=0.008), having moderate home stress (p=0.041) and financial stress (p=0.015) predicted decreased MCS significantly. Predictors in the MCS model explained 36% of the variance in the model. Conclusion: Through the use of a theoretical framework, the Wilson-Cleary model of healthrelated quality of life facilitated a fuller understanding of the several factors impacting H-RQoL and FS. Therefore, it is recommended that large-scale studies investigate the causal relationship between these factors. The study highlights the adverse impact of disability and presence of comorbid diseases on QoL and functional status. The value of the study lies in the fact that assessing how an individual perceives his or her health is necessary to develop appropriate treatment strategies which should lead to positive health outcomes.en_US
dc.description.embargo2022-08-31
dc.identifier.urihttps://hdl.handle.net/10566/19247
dc.language.isoenen_US
dc.publisherUniversity of the Western Capeen_US
dc.rights.holderUniversity of the Western Capeen_US
dc.subjectHypertensionen_US
dc.subjectNon-communicable diseasesen_US
dc.subjectHealth-related quality of life (H-RQoL)en_US
dc.subjectQuality of lifeen_US
dc.subjectSocial supporten_US
dc.subjectStressen_US
dc.subjectAdultsen_US
dc.subjectMiddle-aged adultsen_US
dc.titleInvestigating predictors of health-related quality of life and functional status in middle-aged to older adults with hypertension in a selected urban communityen_US

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