Quality of life in asthmatic outpatients

• Type: Article in International Scientific Journal
• Date: 2008

Authors

lobo, fa (Author) Other; almada-lobo, b (Author) FEUP

Journal

Title: Journal of Asthma

Vol. 45 No. 1

Pages: 27-32

ISSN: 0277-0903

Publisher: Taylor & Francis

Indexing

ISI Web of Knowledge - 16 Citations

Scopus - 18 Citations

Other information

Authenticus ID: P-004-3SQ

DOI: 10.1080/02770900701815495

Abstract (EN): Asthma patients incur a great cost in terms of loss of quality of life. The purpose of this study is to evaluate the relative contribution and relationship of several patient- and disease-related factors, measured by several variables, to the quality of life in adults with asthma. Two hundred and ten asthmatic outpatients over 18 years old, registered in a Family Health Unit, were randomly selected to complete the Asthma Quality of Life (AQLQ) and Short Form Generic questionnaires (SF-36), respectively. Single and multiple linear regression models were developed to explain the variability of the summary scores of AQLQ and Physical and Mental Health SF-36. As potential predictors, the following independent variables were used: gender, age, number of comorbidities, asthma severity following the Global Initiative for Asthma (GINA) criteria, asthma control (measured by ACQ questionnaire), %FEV1 (forced expiratory volume in the first second) and, for the first time, Graffar Score to assess socioeconomical features. The Graffar Score is an index that divides the population in 5 socioeconomic layers. We report the best Adjusted R Square of these models published in the literature, ranging from 0.40 to 0.76. Women showed poorer quality of life than men. The best predictor of AQLQ was ACQ, followed by Asthma Severity, Gender and %FEV1. The best predictors of Physical and Mental Health SF-36 were, by decreasing importance, ACQ, number of comorbidities, Gender and Graffar Score. We note that the variable Dumber of comorbidities was included in both SF-36 models, but not in AQLQ model. Asthma Severity and %FEV1 did not enter into SF-36 models. We conclude that besides clinical and functional measures, the evaluation process of the overall health status must incorporate quality-of-life measures.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 6