Quality of life in Brazil: normative values for the Whoqol-bref in a southern general population sample
- 799 Downloads
Normative data for WHOQOL-bref are scarce in the literature and unavailable in Latin American countries. The main objective of this study was to provide normative scores of WHOQOL-bref in a general population sample in Brazil and to describe differences in mean scores according to some socio-demographic characteristics.
WHOQOL-bref was applied to a randomly selected sample of the general population of Porto Alegre. Participants were literate people aged 20 to 64 years. The questionnaires were self-administered in the presence of an interviewer in the respondent’s home.
The response rate was 68%, and the final sample contained 751 respondents (38% men, 62% women). Low quality of life was observed in the following subgroups: female gender, lower economic class, lower educational level, and the subgroup reporting a chronic medical condition. The mean scores of the WHOQOL-bref and percentiles of scores are reported as normative data for the general population.
Our results can be useful to researchers using the WHOQOL-bref to compare their results with normative data from a randomly selected sample of general population. Additionally, the ability of WHOQOL-bref to discriminate different population subgroups makes it an important tool to identify vulnerable groups in epidemiological surveys.
KeywordsQuality of life WHOQOL-bref Normative data Brazil
World health organization quality of life instrument
Quality of life
Gross domestic product
Brazilian institute of geography and statistics
Statistical package for social sciences
We thank the Research Incentive and Event Fund of Hospital de Clínicas de Porto Alegre for the financial aid in translating this article. Dr. Luciane Cruz received graduate research scholarship from Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES), Brazil. Prof. Polanczyk and Prof. Fleck received a research scholarship from Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)/Brazil. This study was funded by CNPQ/Brazil (Edital MCT-CNPq/MS-SCTIE-DECIT No 36/2005).
- 1.Wilson, I. B., Cleary, P. D. (1995). Linking clinical variables with health-related quality of life. A conceptual model of patient outcomes. The Journal of the American Medical Association, 273(1), 59–65.Google Scholar
- 4.The World Health Organization Quality of Life Assessment (WHOQOL): Development and general psychometric properties (1998) Social Science & Medicine, 46(12), 1569–1585.Google Scholar
- 5.Fleck, M. P., Louzada, S., Xavier, M., Chachamovich, E., Vieira, G., Santos, L., et al. (1999). Application of the Portuguese version of the instrument for the assessment of quality of life of the World Health Organization (WHOQOL-100). Revista de Saude Publica, 33(2), 198–205.PubMedCrossRefGoogle Scholar
- 6.Fayers, P. M., & Machin, D. (2007). Quality of life. The assessment, analysis and interpretation of patient-reported outcomes (2nd ed.). West Sussex, England: Wiley.Google Scholar
- 9.IBGE Cidades. Instituto Brasileiro de Geografia e Estatística (IBGE) Available from: www.ibge.gov.br. Last update 12.02.10.
- 10.Critério Econômico Brasil (2003). Associação Brasileira de Empresas de Pesquisa. Available from: www.abep.org/novo/default.aspx. Last update 12.02.10.
- 11.Skevington, S. M., Lotfy, M., O’Connell, K. A. (2004). The World Health Organization’s WHOQOL-BRIEF quality of life assessment: Psychometric properties and results of the international field trial. A report from the WHOQOL-group. Quality of Life Research, 13(2), 299–310.Google Scholar
- 12.Gandek, B., Ware, J. E., Jr. (1998). Methods for validating and norming translations of health status questionnaires: The IQOLA Project approach. International Quality of Life Assessment. Journal of Clinlical Epidemiology 51(11), 953–959.Google Scholar