Importance of Sociodemographic and Morbidity Aspects in Measuring Health-Related Quality of Life: Performances of Three Tools: Comparison of Three Questionnaire Scores

• Published in: The European journal of health economics 2009-10, Vol.10 (4), p.389-397
• Main Authors: Quercioli, Cecilia, Messina, Gabriele, Barbini, Emanuela, Carriero, Giovanni, Fanì, Mara, Nante, Nicola
• Format: Article
• Language: English
• Subjects: Adult; Aged; Agreements; Algorithms; Body mass index; Chronic diseases; Chronic illnesses; Comparative analysis; Cross-Sectional Studies; Demographics; Demography; Diabetes; Economic Policy; Education; Female; General practice; Health Care Management; Health Economics; Health status; Health Status Indicators; Humans; Hypertension; Investigations; Italy - epidemiology; Male; Medicine; Medicine & Public Health; Middle Aged; Morbidity; Musculoskeletal diseases; Original Paper; Patients; Pharmacoeconomics and Health Outcomes; Population; Public Finance; Public Health; Quality of Life; Questionnaires; Regression coefficients; Sociodemographics; Studies; Surveys and Questionnaires - standards
• ISSN: 1618-7598; 1618-7601
• DOI: 10.1007/s10198-008-0139-9

Background Since health-related quality of life (HRQL) measures are numerous, comparisons have been suggested. Aim To compare three HRQL measures: SF6D, HUB and EQ5D. Methods Three questionnaires (SF36, HUI3, EQ5D) were administered to 1,011 patients attending 16 general practices in two Italian cities. Information about patients' gender, age, education, marital status, smoking, body mass index (BMI) and chronic diseases (hypertension, diabetes, cardiovascular and musculoskeletal diseases) were also collected. Questionnaires scores were calculated using the appropriate algorithms; in particular SF6D scores were obtained from SF36 items. Agreement and correlation between questionnaires scores were investigated using Bland and Altman method and Spearman coefficient. The influence of sociodemographic and morbidity indicators on scores was analysed using the nonparametric quantile regression. Results The Spearman coefficient was about 0.6 for all questionnaires. The 95% limits of agreement of the scores were approximately from —0.5 to 0.3 except for SF6D and EQ5D when they were from —0.4 to 0.2. The measures were influenced by socio-demographic and clinical variables in a similar way, especially SF6D (the index obtained from SF36) and EQ5D, which appeared to be influenced by the same pattern of factors, including gender, chronic diseases, smoking and BMI. Conclusions Overall, the agreement between questionnaires scores was quite low, whilst the correlation level was good. Questionnaire scores were influenced by socio-demographic and clinical variables in a similar way, especially SF6D and EQ5D. Therefore, the descriptive capacity of SF6D and EQ5D was found to be similar.