Quality of life among an Iranian general population sample using the World Health Organization’s quality of life instrument (WHOQOL-BREF)

Naieni, Kourosh Holakouie; Mohammad, Kazem; Majdzadeh, Reza; Montazeri, Ali

doi:10.1007/s00038-010-0174-z

Cited by 48 publications

(47 citation statements)

References 21 publications

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“…As previously noted in the literature, numerous variables were associated with an increased prevalence of poor quality of life in general, and in the four domains, including individual characteristics and job characteristics, lifestyle and general health variables: increased age [43], income [44], being female [20]; education level [45], living without a partner [39], being dissatisfied at work, being middle level and contracted [46], having lower levels of physical activity and smoking heavily [47], negative self-perceived health, having common mental illnesses [48], and having diseases diagnosed by a physician. The variables associated with each domain provide evidence for their different constructs and determinants.…”

Section: Discussionmentioning

confidence: 99%

Psychosocial work conditions and quality of life among primary health care employees: a cross sectional study

Teles

Barbosa

Vargas

et al. 2014

Health Qual Life Outcomes

116

102

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BackgroundWorkers in Primary Health Care are often exposed to stressful conditions at work. This study investigated the association between adverse psychosocial work conditions and poor quality of life among Primary Health Care workers.MethodsThis cross-sectional study included all 797 Primary Health Care workers of a medium-sized city, Brazil: doctors, nurses, nursing technicians and nursing assistants, dentists, oral health technicians, and auxiliary oral hygienists, and community health workers. Data were collected by interviews. Quality of life was assessed using the WHOQOL-BREF; general quality of life, as well as the physical, psychological, social and environmental domains were considered, with scores from 0 to 100. Higher scores indicate a better quality of life. Poor quality of life was defined by the lowest quartiles of the WHOQOL score distributions for each of the domains. Adverse psychosocial work conditions were investigated by the Effort-Reward Imbalance model. Associations were verified using multiple logistic regression.ResultsPoor quality of life was observed in 117 (15.4%) workers. Workers with imbalanced effort-reward (high effort/low reward) had an increased probability of general poor quality of life (OR = 1.91; 1.07–3.42), and in the physical (OR = 1.62; 1.02–2.66), and environmental (OR = 2.39; 1.37–4.16) domains; those with low effort/low reward demonstrated a greater probability of poor quality of life in the social domain (OR = 1.82; 1.00–3.30). Workers with overcommitment at work had an increased likelihood of poor quality of life in the physical (OR = 1.55, 1.06–2.26) and environmental (OR = 1.69; 1.08–2.65) domains. These associations were independent of individual characteristics, job characteristics, lifestyle, perception of general health, or psychological and biological functions.ConclusionsThere is an association between adverse psychosocial work conditions and poor quality of life among Primary Health Care workers.

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Section: Discussionmentioning

confidence: 99%

Psychosocial work conditions and quality of life among primary health care employees: a cross sectional study

Teles

Barbosa

Vargas

et al. 2014

Health Qual Life Outcomes

116

102

View full text Add to dashboard Cite

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“…In order to the validity of the instrument for assessment QOL among the hypertensive patients, Cronbach’s alpha was used to estimate the reliability of the WHOQOL-BREF. Based on other studies, Cronbach’s alpha values of 0.70 and over were deemed acceptable [21, 26]. Pearson’s correlation coefficient was used to determine the level of agreement between the four domains of the WHOQOL-BREF.…”

Section: Methodsmentioning

confidence: 99%

Quality of life among people living with hypertension in a rural Vietnam community

Ha¹,

Duy²,

Le³

et al. 2014

BMC Public Health

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BackgroundTo respond to growing prevalence of hypertension in Vietnam, it is critical to have an in-depth understanding about quality of life (QOL) among people living with hypertension and related factors. This study aimed to measure QOL among hypertensive people in a rural community in Vietnam, and its association with socio-demographic characteristics and factors related to treatment.MethodsThis study was conducted in a rural community located 60 km from Ho Chi Minh City. Face-to-face interviews were conducted among 275 hypertensive people aged 50 years and above using WHOQOL-BREF questionnaire. Descriptive statistics were used to examine mean scores of quality of life. Cronbach’s alpha coefficient and Pearson’s correlation coefficient were applied to estimate the internal consistency, and the level of agreement between different domains of WHOQOL-BREF, respectively. Independent T-test and ANOVA test followed by multiple linear regression analyses were used to measure the association between QOL domains and independent variables.ResultsBoth overall WHOQOL-BREF and each domain had a good internal consistency, ranging from 0.65 to 0.88. The QOL among hypertensive patients was found moderate in all domains, except for psychological domain that was fairly low (mean = 49.4). Backward multiple linear regressions revealed that being men, married, attainment of higher education, having physical activities at moderate level, and adherence to treatment were positively associated with QOL. However, older age and presence of co-morbidity were negatively associated with QOL.ConclusionWHOQOL-BREF is a reliable instrument to measure QOL among hypertensive patients. The results revealed low QOL in psychological domain and inequality in QOL across socio-demographic characteristics. Given the results, encouraging physical activities and strengthening treatment adherence should be considered to improve QOL of hypertensive people, especially for psychological aspect. Actions to improve QOL among hypertensive patients targeted towards women, lower educated and unmarried patients are needed in the setting.

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“…The environment had the lowest mean among all HRQOL domains, a finding that has been reported in previous studies (Nedjat et al ., ; Taghavi et al ., ; Teles et al ., ). A poor environment may be related to the high‐risk and potentially unsafe and unhealthy occupational environment that construction industrial workers are exposed to (Reese & Edison, ; Taghavi et al ., ).…”

Section: Discussionmentioning

confidence: 99%

Predictors of health‐related quality of life among industrial workers: A descriptive correlational study

Malak

2017

Nursing & Health Sciences

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Assessment and evaluation of the health-related quality of life of industrial workers is an important research focus. This descriptive correlational study identifies the predictors of health-related quality of life using a random sampling of industrial workers (n = 640) from construction factories in Amman Governorate in Jordan using demographic characteristics, a health and work-related factors questionnaire, and the World Health Organization Quality of Life-Brief scale. Results showed that industrial workers had good physical health but a poor working environment. There was a statistically significant relationship between educational level, conflict between work and individual life and work and social life, working hours, and workload, and all domains of health-related quality of life. Overall, educational level was the main predictor for all domains of health-related quality of life. Such results confirm the need to develop appropriate interventions and strategies to improve workers' health-related quality of life. Furthermore, developing an integrated approach among policymakers, employers, and work organizations to enhance industrial workers' occupational health programs could be effective.

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Quality of life among an Iranian general population sample using the World Health Organization’s quality of life instrument (WHOQOL-BREF)

Abstract: Overall, quality of life scores were found to be low among an Iranian general population and greatly varied by socio-demographic variables. In addition, self-reported health condition was found to be the strongest factor affecting people's quality of life.

Cited by 48 publications

References 21 publications

Psychosocial work conditions and quality of life among primary health care employees: a cross sectional study

Psychosocial work conditions and quality of life among primary health care employees: a cross sectional study

Quality of life among people living with hypertension in a rural Vietnam community

Predictors of health‐related quality of life among industrial workers: A descriptive correlational study

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