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Impact of chronic obstructive pulmonary disease on exercise capacity, physical activity and quality of life in a community center

Grant number: 13/16951-4
Support Opportunities:Regular Research Grants
Duration: December 01, 2013 - November 30, 2014
Field of knowledge:Health Sciences - Medicine - Medical Clinics
Principal Investigator:Elcio dos Santos Oliveira Vianna
Grantee:Elcio dos Santos Oliveira Vianna
Host Institution: Faculdade de Medicina de Ribeirão Preto (FMRP). Universidade de São Paulo (USP). Ribeirão Preto , SP, Brazil

Abstract

The chronic obstructive pulmonary disease (COPD) is a highly prevalent disease in individuals aged over 40 years. It is a disease with increasing social and economic impact Objectives: To understand the characteristics of COPD, the frequency of underdiagnosis, the influence of the disease on the quality of life, employment status, exercise capacity and physical activity in a community center. Method: It is an observational, analytical and cross-sectional study conducted in a municipal community center with individuals aged 50 years or older. At least 300 randomly selected participants will answer questionnaires on demographic, socioeconomic, labor characteristics, quality of life, symptoms and health status. Anthropometric evaluation, spirometry and 6-minute walking test will also be carried out. COPD patients will be identified by symptoms and by obstruction in spirometry (FEV1/FVC < 0.70 and FEV1 below 80% predicted values). Patients with COPD who report previous physician-made diagnosis of COPD will be compared with patients without previous diagnosis in order to evaluate frequency of under-diagnosis and characteristics associated with previous diagnosis. We will use the unpaired two-tailed Student t-test to compare two independent groups: COPD group and the group without COPD; or, COPD group previously diagnosed and group with COPD undiagnosed. To compare proportions of variables between two independent groups, we will use chi-square test. Logistic regression and multiple logistic regression will be used to identify associations between the independent variables (such as socioeconomic status) and the dependent variable (such as previous diagnosis of COPD). Simple logistic regression and multiple analyses will be carried out to identify independent variables that could provide significant changes (explanatory) in the response variable (quality of life, 6-min walked distance or employment status). We expect to know relevant characteristics of COPD in a population group that has not been referred to medical system, but that attends a public community institution for leisure and social life. With these data, we will understand the potential of these centers for COPD detection to diminish its risks. (AU)

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