Quality of life and its predictive factors in adolescents with type 1 Diabetes mellitus

• Grant number: 08/05274-3
• Support type: Regular Research Grants
• Duration: November 01, 2008 - October 31, 2010
• Field of knowledge: Health Sciences - Nursing - Medical-Surgical Nursing
• Cooperation agreement: CNPq - PPSUS
• Principal researcher: Sonia Aurora Alves Grossi
• Grantee: Sonia Aurora Alves Grossi
• Home Institution: Escola de Enfermagem (EE). Universidade de São Paulo (USP). São Paulo , SP, Brazil

Abstract

The Diabetes Mellitus is, currently, one of the most prevalent chronic diseases. Type 1 Diabetes (DM1) is not the most incident in the world population, but is one of the most prevalent diseases in infancy and adolescence. Adolescence is a phase of physiological and psychosocial brusque changes. Adolescent with type 1 Diabetes must deal with these transformations and with behavioral changes demanded by the disease conviviality. Besides, the treatment implies in the adoption of new habits not always easily incorporated in this phase of development. The evaluation of Health Related Quality of Life (HRQL), in set with the glycemic control therapy, has been presented as an important tool of evaluation of the disease impact and the treatment strategies, which serve as a support for the disease management and adherence to the treatment. The aims of this study are: to evaluate the HRQL of adolescent with DM1 and to identify the predictive factors of HRQL of adolescents with DM1 in different phases of the disease (honeymoon and chronic phase). The study will be carried through in the Children with Diabetes Institute in Porto Alegre,RS, Brazil, which is a reference center in the treatment of adolescents with type 1 Diabetes. The population of the study will be composed by adolescents with DM1, aged from 10 to 19 years old. The sample will be composed by 270 youths selected by drawing. Youths should respond to the questionnaires: Diabetes Quality of Life for Youths, Brazilian version, Rosenberg Self-Steem Instrument and Socio-demographic and Clinic data Formulary for the evaluation of the predictive variables of HRQL. The intention is to use the Generalized Linear Model for the data analyses. (AU)