P-473: Relationship between body composition and physical activity on glycemic control in children and adolescents with type 1 diabetes
L Coutinho de Azevedo, E Y Azevedo Campanella, D M VargasAbstract
Introduction
Abnormalities in body composition (BC) and physical activity (PA) in people with type 1 diabetes (T1DM) can impair glycemic control and increase susceptibility to long-term complications.
Objectives
To analyse the relationship between glycated haemoglobin (HbA1c), components of the BC e PA in children and adolescents with T1DM.
Methods
This cross-sectional study included 38 participants aged 5–19 years with T1DM receiving care at a specialized public health service in southern Brazil. Age, HbA1c levels, and weekly frequency of scheduled PA were collected. The BC was assessed using bioelectrical impedance analysis, with evaluation of fat and lean mass. Multivariate linear regression analyses were used in two models, with HbA1c as the dependent variable.
Results
The participants had mean values for age, HbA1c, and scheduled PA of 12.9 years, 9.1%, and 3.2 days per week, respectively. Model 1 revealed statistical significance in the multivariate regressions for skeletal muscle mass index (SMMI), fat mass index (FMI), trunk fat mass (TFM%), and visceral fat level (VFL), explaining approximately 30% of the variation in HbA1c levels. Age showed a positive and significant association with HbA1c, while the components of the CC (SBMM, FMI, TFM%, and VFL) showed a positive coefficient, although without statistical significance. The addition of weekly scheduled PA frequency to Model 1 maintained statistical significance in the relationships, increasing the explanatory power of the models by 6–7%. Scheduled PA showed an inverse association with HbA1c in all relationships, although it did not reach statistical significance.
Conclusions
The main determinant of glycemic control in the study sample was age. Body fat and muscle mass did not show a significant independent contribution to the variation in HbA1c. The frequency of scheduled PA increased the explanatory power of the models, though this was not statistically significant.