The Association between Dietary Pattern, Obesity, and Glycemic Control of Children and Adolescents with Type 1 Diabetes Mellitus.

AIMS: To evaluate the association between dietary patterns, obesity, and glycemic control in children and adolescents with type 1 diabetes mellitus (T1DM). METHODS: A cross-sectional study was carried out in 2015 at a diabetes reference center in Rio de Janeiro. Sociodemographic data and those related to outpatient follow-ups were obtained from the medical records. The assessment of food consumption was performed using a 24 h food recall. Obesity was defined as body mass index-for-age (BMI-for-age) ≥ +1 z-score. Glycemic control was assessed using glycated hemoglobin (HbA1c). Dietary patterns were generated by factorial analysis, and each individual's adherence to these dietary patterns was determined by the factor loadings and then classified into terciles. RESULTS: The study population included 120 children and adolescents, among whom 5 dietary patterns were identified. The prevalence of obesity was 31.7% (n = 38), and 64.2% (n = 77) of the participants had inadequate glycemic control. We observed that individuals with higher adherence to dietary pattern five, characterized by a greater consumption of ultra-processed foods, had higher odds of having higher HbA1c levels (OR = 3.49; 95% CI = 1.18-11.16). CONCLUSIONS: Higher consumption of ultra-processed foods can be detrimental to glycemic control in children and adolescents. Thus, food intake monitoring is of paramount importance as part of the multidisciplinary care of patients with T1DM.

Determinants of ultra-processed food consumption in Brazilian children and adolescents with type 1 diabetes mellitus: a cross-sectional study.

OBJECTIVES: To analyze the determinants of UPP consumption among children and adolescents with type 1 diabetes mellitus. METHODS: Cross-sectional study at a reference hospital for the treatment of diabetes in Rio de Janeiro, Brazil. The sociodemographic, anthropometric, dietary, and clinical factors associated with the percentage of total energy intake (TEI) consumed in the form of UPP were investigated. Food consumption was assessed by 24 h recall and the foods were classified according to the degree of processing as described in the NOVA classification, after which the TEI of each food group was calculated. Multiple linear regression was adopted in the analysis, and associations with p<0.05 were considered significant. RESULTS: The study included 120 children and adolescents with a mean age of 11.74 ± 2.88 years, 53.3% female. Body mass index z-score was 0.65 (± 0.89) and 31.7% (n=38) were overweight. The average total energy consumption was 1,756.38 kcal (± 518.38). The mean percentage of TEI from UPP was 24.2% ± 17.9, meaning that 425.59 kcal (± 380.15) of all calories ingested came from such foods. The independent variables associated with the percentage of ultra-processed foods (UPP) in TEI were: per capita household income up to one the minimum wage (ß: -22.03; CI 95% -35.24 to -8.82); and parents/guardians schooling of the up to nine years in formal education (ß: 19.86; CI 95% 8.27-31.45). CONCLUSIONS: Lower household income and fewer years in formal education seem to determine a preference for UPP over fresh and minimally processed foods.

Predictive factors of non-HDL cholesterol in children and adolescents with type 1 diabetes mellitius: A cross-sectional study.

AIMS: To assess predictors of non-HDL cholesterol in children and adolescents with T1DM. METHODS: A cross-sectional study of 120 children and adolescents aged 7-16 with T1DM, but without any other chronic morbidities, at a referral outpatient clinic for the treatment of diabetes in Rio de Janeiro, Brazil. Socio-demographic, anthropometric, dietary, and clinical factors were assessed, which included measurements of serum lipids and glycated hemoglobin (HbA1c). Food intake was assessed by 24-h dietary recall. Multiple linear regression was adopted in the analysis. RESULTS: The mean age of of the subjects was 11.74 ±â€¯2.88 years, 53.3% were female, and the mean duration of T1DM was 6.68 ±â€¯3.33 years. The mean energy intake from carbohydrates, proteins, and lipids was 51.98% (±9.20), 21.43% (±6.13), and 26.57% (±9.98), respectively. The energy intake from processed and ultra-processed foods represented 40.79% of total energy intake. The predictors of non-HDL cholesterol were: HbA1c (%) (p = 0.000, ß = 8.5, CI: 4.8-12.1), duration of T1DM (p = 0.000, ß = 2.8, CI: 1.3-4.3), and sex (p = 0.032, ß = 10.1, CI: 0.9-19.4). CONCLUSION: Glycemic control was the major modifiable predictor of non-HDL cholesterol concentrations, a significant indicator of cardiovascular risk.

Predictor factors of glycemic control in children and adolescents with type 1 diabetes mellitus treated at a referral service in Rio de Janeiro, Brazil.

AIM: To evaluate the predictive factors of glycemic control in children and adolescents with type 1 diabetes mellitus (T1DM). METHODS: Cross-sectional study at a referral service in Rio de Janeiro, Brazil. Sociodemographic, anthropometric, clinical, and dietary factors were evaluated. Food consumption was evaluated by 24 h dietary recall and the NOVA system was adopted for classifying the foods according to the extent and purpose of industrial processing. The predictive factors were evaluated by multivariate linear regression, adopting p < 0.05. RESULTS: One hundred and twenty children and adolescents participated, with a mean age of 11.74 years (±2.88) and HbA1c of 8.13% (±1.26). The mean diabetes duration was 6.68 years (±3.33) and the insulin used was 1.05 units per kilogram of ideal weight (IU/kg of ideal weight; ±0.46) About 80% (n = 96) used carbohydrate counting and it was verified that 24.27% (±17.89) of the participants' total calories came from ultraprocessed foods. For each year of diagnosis with T1DM and for each IU/kg of weight used, HbA1c increased by 0.087% (ß = 0.087, p = 0.007) and 0.651%, respectively (ß = 0.651; p = <0.001). Use of carbohydrate counting was associated with a 1.058% reduction in HbA1c (ß = -1.058; p = 0.001). CONCLUSION: Disease duration and insulin dose were directly reflected in HbA1c concentrations, while carbohydrate counting showed an inverse association.