Carbohydrate counting as a strategy to optimize glycemic control in type 1 diabetes mellitus

ABSTRACT Objective: The objective of this study was to verify the impact of carbohydrate counting (CC) on glycemic control and body weight variation (primary and secondary outcomes, respectively) between consultations in patients with diabetes mellitus (T1D) followed at a tertiary hospital in southern Brazil in a public health system environment. We also sought to investigate CC adherence. Materials and methods: This retrospective cohort study included 232 patients with T1D who underwent nutritional monitoring at a referral hospital for diabetes care between 2014 and 2018. To assess primary and secondary outcomes, data from 229 patients, 49 of whom underwent CC during this period and 180 individuals who used fixed doses of insulin, were analyzed. The impact of CC on glycemic control was assessed with the mean glycated hemoglobin (HbA1c) level at all consultations during the follow-up period. Results: In the model adjusted for the most confounders (except pregnancy), the mean HbA1c was better in the CC group (8.66 ± 0.4% vs. 9.36 ± 0.39%; p = 0.016), and body weight variation was lower (0.13 ± 0.28 kg vs. 0.53 ± 0.24 kg; p = 0.024). Adherence to CC was reported in 69.2% of consultations. Conclusion: CC optimized the glycemic control of individuals with T1D, resulting in less weight variation than in the fixed insulin dose group, which indicates that CC is an important care strategy for these patients.

Body adiposity markers and insulin resistance in patients with type 1 diabetes

ABSTRACT Objectives: Body composition changes are associated with adverse effects such as increased insulin resistance (IR) in individuals with diabetes mellitus. This study aims to evaluate the association between different body adiposity markers and IR in adults with type 1 diabetes (T1D). Subjects and methods: The cross-sectional study included outpatient adults with T1D from a university public hospital in southern Brazil. The body adiposity markers studied were waist circumference (WC), waist-height ratio (WHtR), body mass index (BMI), conicity index (CI), lipid accumulation product (LAP) and body adiposity index (BAI). IR was calculated using an Estimated Glucose Disposal Rate (EGDR) equation (analyzed in tertiles), considering an inverse relation between EGDR and IR. Poisson regression models were used to estimate the odds ratio (OR) and 95% CIs of association of adiposity markers with IR. Results: A total of 128 patients were enrolled (51% women), with a median EGDR of 7.2 (4.4-8.7) mg.kg−1.min−1. EGDR was negatively correlated with WC (r = −0.36, p < 0.01), WHtR (r = −0.39, p < 0.01), CI (r = −0.44, p < 0.01), LAP (r = −0.41, p < 0.01) and BMI (r = −0.24, p < 0.01). After regression analyses, WC (OR = 2.07; CIs: 1.12-3.337; p = 0.003), WHtR (OR = 2.77; CIs: 1.59-4.79; p < 0.001), CI (OR = 2.59; CIs: 1.43-4.66; p = 0.002), LAP (OR = 2.27; CIs: 1.25-4.11; p = 0.007) and BMI (OR = 1.78; CIs: 1.09-2.91; p = 0.019) remained associated with IR. Conclusions: The authors suggest using the studied adiposity markers as a routine since they were shown to be suitable parameters in association with IR.

Association between fixed night work and obesity: a systematic literature review

This systematic review aimed to evaluate the association between fixed night work and overweight or weight gain. PubMed and EMBASE were searched until October 2021 for studies evaluating the association between fixed night work patterns and the risk of overweight or obesity (for cross-sectional designs) or weight gain (for longitudinal designs). The outcomes extracted were mean body mass index (BMI), mean BMI difference, overweight %, obesity %, odds ratio, relative risk, and prevalence ratio. The quality of the report was evaluated using the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) checklist. The protocol was registered at PROSPERO (# 42017080515). In total, 25 studies met the inclusion criteria. All studies were observational, 16 were cross-sectional, three were cohorts (two also had baseline cross-sectional data), and the other eight were cross-sectional at baseline and had longitudinal follow-up studies (six prospective cohorts, one retrospective, one interventional). Most had good reporting quality. The fixed night work definition and weight outcomes varied according to the different studies. Most of them found an association between fixed night work and overweight, obesity, or weight gain. This systematic review reinforces the evidence that fixed night work is associated with overweight or obesity, and prolonged night work exposure leads to weight gain. Future research should be conducted with more accurate measures and a prospective design. Fixed night workers should be monitored and advised, especially those with prolonged exposure.

Higher fiber intake is associated with lower blood pressure levels in patients with type 1 diabetes

ABSTRACT Objective The present investigation sought to evaluate the potential association between dietary fiber intake and blood pressure (BP) in adult patients with type 1 diabetes (T1D). Subjects and methods A cross-sectional study was carried out in 111 outpatients with T1D from Porto Alegre, Brazil. Patients were predominantly male (56%) and white (88%), with a mean age of 40 ± 10 years, diabetes duration of 18 ± 9 years, BMI 24.8 ± 3.85 kg/m2, and HbA1c 9.0 ± 2.0%. After clinical and laboratory evaluation, dietary intake was evaluated by 3-day weighed-diet records, whose reliability was confirmed by 24-h urinary nitrogen output. Patients were stratified into two groups according to adequacy of fiber intake in relation to American Diabetes Association (ADA) recommendations: below recommended daily intake (< 14g fiber/1000 kcal) or at/above recommended intake (≥ 14g/1000 kcal). Results Patients in the higher fiber intake group exhibited significantly lower systolic (SBP) (115.9 ± 12.2 vs 125.1 ± 25.0 mmHg, p = 0.016) and diastolic blood pressure (DBP) (72.9 ± 9.2 vs 78.5 ± 9.3 mmHg, p = 0.009), higher energy intake (2164.0 ± 626.0 vs 1632.8 ± 502.0 kcal, p < 0.001), and lower BMI (24.4 ± 3.5 vs 26.2 ± 4.8, p = 0.044). Linear regression modelling, adjusted for age, energy intake, sodium intake, and BMI, indicated that higher fiber intake was associated with lower SBP and DBP levels. No significant between-group differences were observed with regard to duration of diabetes, glycemic control, insulin dosage, or presence of hypertension, nephropathy, or retinopathy. Conclusion We conclude that fiber consumption meeting or exceeding current ADA recommendations is associated with lower SBP and DBP in patients with T1D.