Detalhes bibliográficos
| Ano de defesa: |
2017 |
| Autor(a) principal: |
Rebesco, Denise Barth
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| Orientador(a): |
Mascarenhas, Luis Paulo Gomes
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| Banca de defesa: |
Não Informado pela instituição |
| Tipo de documento: |
Dissertação
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| Tipo de acesso: |
Acesso aberto |
| Idioma: |
por |
| Instituição de defesa: |
Universidade Estadual do Centro-Oeste
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| Programa de Pós-Graduação: |
Programa de Pós-Graduação em Desenvolvimento Comunitário (Mestrado Interdisciplinar)
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| Departamento: |
Unicentro::Departamento de Saúde de Irati
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| País: |
Brasil
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| Palavras-chave em Português: |
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| Palavras-chave em Inglês: |
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| Área do conhecimento CNPq: |
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| Link de acesso: |
http://tede.unicentro.br:8080/jspui/handle/jspui/1465
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Resumo: |
The professionals involved in the treatment of patients with type 1 diabetes mellitus need to understand the glycemic variability in order to aim its reduction, since it seems to contribute to the sending of complications, which is, therefore, a requirement of good glycemic control. Since the physiological interactions between variability and physical activity in patients with type 1 diabetes can interfere in the quality of life and sleep quality of these patients. The objective of this study was to verify the relationship between physical activity, quality of life and sleep quality with glycemic variability in adolescents with type 1 diabetes. The sample consisted of 34 adolescents with type 1 diabetes mellitus, who performed blood collection for glycated hemoglobin analysis and anthropometric evaluation to obtain height, weight and BMI. The adolescents answered to the WHOQOL-bref questionnaire for assessment of quality of life and the Pittsburgh sleep quality index for assessment of sleep quality. To assess the level of physical activity and identify the more and less active day, the adolescents used an accelerometer (Actgraph® wGT3X) fixed at the waist for five days, recording data referring to physical activity daily routine. In the same period, a continuous glucose monitoring (GUARDIAN®REAL Time MEDTRONIC) was used. After the collection the EasyGV worksheet was used to calculate the glycemic variability indicators: Low Blood Glucose Index (LBGI), High Blood Glucose Index (HBGI), Mean amplitude of glycemic excursions (MAGE) e Glycemic Risk Assessment in Diabetes Equation (GRADE). As for the statistical analyzes, normality analyzes are performed through the Shapiro-Wilk test and correlation analysis through the Speraman test. Chi-square test was used to identify differences in the proportions between boys and girls. A linear regression test was used to determine a conditional of the dependent variables on the independent variable. To verify if there was a difference between the more and less active day, as well as in the glycemic variability between the days, Studant test was used, as well as to verify differences between genders. In addition, an ANOVA test was performed to verify whether the difference in glycemic variability of groups that performed different daily averages of moderate to vigorous physical activity. All testes adopted α of 0.05. The participants had similar age (13.04 ± 1.94 years), weight (47.85 ± 13.16 kg), height (153.90 ± 13.19 cm) and BMI-Z score (0.34 ± 0.87). The assessment of quality of life revealed differences between boys and girls for the physical domain (79.46 ± 8.30 vs. 71.82 ± 10.74). Physical activity data revealed a large proportion of time spent in sedentary behavior. The assessment of glycemic variability classifies most of the participants without the normal range. However, glycemic variability was evaluated on days with different volumes of moderate to vigorous physical activity and no significant difference was observed. In addition, glycemic variability showed direct correlation with moderate to vigorous physical activity and inverse correlation with sleep quality. It was concluded that moderate to vigorous physical activity explains 10.7% of the LBGI variation and 14.4% of the HBGI variation. Similarly, 17.4% of sleep quality is explained by the HBGI, DP and MAGE indicators. By comparing glycemic variability in more and less active days, it is suggested that the increase in the amount of moderate to vigorous physical activity in the routine of adolescents with diabetes does not influence the increases in the glycemic variability, so, there are no dose-response relationship between these variables. |
