Copper Deficiency Associated with Glycemic Control in Individuals with Type 2 Diabetes Mellitus.

Adequate copper (Cu) status has been associated with improved glycemic control, partly because of its role in reducing oxidative stress through superoxide dismutase (SOD) activity. Thus, the aim was to investigate the relationship between plasma Cu concentration and markers associated with glycemic control in individuals with type 2 diabetes mellitus (T2DM). This observational and cross-sectional study was conducted in individuals with T2DM of both sexes, aged between 19 and 59 years. Plasma Cu levels were analyzed using inductively coupled plasma optical emission spectrometry (ICP-OES). Fasting glucose and insulin concentrations, C-peptide levels, SOD activity, and glycated hemoglobin (%HbA1c) were measured. Homeostatic model assessments (HOMA%B, HOMA%S, and HOMA-IR) were also performed. Additionally, %body fat and waist circumference were measured, and body mass index was calculated. Participants were categorized based on their plasma Cu concentrations (< 70 µg/dL and ≥ 70 µg/dL). The associations between variables were analyzed using chi-squared or Fisher's test and binary logistic regression models. Statistical significance was set at P < 0.05. Of the 97 participants (74.2% women), 85.5% had Cu deficiency. Cu-deficient individuals showed elevated C-peptide concentrations and HOMA%B values compared to those with adequate Cu levels (2.8 ng/mL vs. 1.8 ng/mL, P = 0.011; and 71.4 vs. 31.0, P = 0.003), respectively. Cu deficiency was associated with insulin resistance (P = 0.044) and decreased likelihood of exceeding the target serum glucose level (OR = 0.147, P = 0.013). However, no significant association was found between SOD activity and plasma Cu concentration. Consequently, Cu deficiency was linked to improved glycemic control, although it was not associated with the other markers.

Association between circulating micronutrient pattern, glycemic control, and insulin resistance in type 2 diabetes mellitus.

The circulating micronutrient pattern in type 2 diabetes mellitus (T2DM) may impact glycemic control and insulin resistance; however, there is a scarcity of studies that have evaluated the circulating micronutrient pattern in the T2DM population. Therefore, our objective was to identify circulating micronutrient pattern and their association with markers of glycemic control and insulin resistance in individuals with T2DM. We developed a cross-sectional observational study involving adults with T2DM in Sergipe, Brazil. We assessed plasma levels of magnesium, zinc, calcium, potassium, and serum 25-hydroxyvitamin D. Additionally, also measured fasting glucose levels, the percentage of glycated hemoglobin (%HbA1c), and calculated the homeostatic model assessment for insulin resistance (HOMA-IR). Patterns of body reserve were established using principal component analysis and categorized into quartiles. Binary logistic regression models were employed. We evaluated 114 individuals (63.7% women), with a median age and body mass index of 49 years and 29.6 kg/m², respectively. Two circulating micronutrient patterns were identified, explaining 62.5% of the variance: Pattern 1 (positive contributions from magnesium, zinc, calcium, and potassium) and Pattern 2 (positive contributions from 25-hydroxyvitamin D and zinc, with a negative contribution from potassium). Lowest quartile for Pattern 1 and Pattern 2 exhibiting a 4.32-fold (p = 0.019) and 3.97-fold (p = 0.038) higher likelihood of increasing HOMA-IR and %HbA1c values, respectively, compared to the larger quartiles. However, no associations were found between these patterns and fasting glucose values. Lowest quartile for both patterns of micronutrients was associated with inadequate metabolic control in individuals with T2DM.

Magnesium Status and Dietary Patterns Associated with Glycemic Control in Individuals with Type 2 Diabetes Mellitus.

Hypomagnesemia and unhealthy eating patterns are associated with poor glycemic control in individuals with type 2 diabetes mellitus (T2DM). This study aimed to associate magnesium status and dietary patterns with glycemic control in T2DM individuals. This cross-sectional study included 147 individuals with T2DM, aged between 19 and 59 years, of both sexes, residents in Sergipe/Brazil. The BMI, waist circumference, %body fat, plasma magnesium, serum glucose, insulin, %HbA1c, triacylglycerol, total cholesterol, LDL-c, and HDL-c were analyzed. Eating patterns were identified using a 24-h recall method. Logistic regression models were used to verify the association of magnesium status and dietary patterns with markers of glycemic control by adjusting for sex, age, time of T2DM diagnosis, and BMI. A P value < 0.05 was considered significant. Magnesium deficiency increased the chance of elevated %HbA1c by 5.893-fold (P = 0.041). Three main dietary patterns were identified: mixed (MDP), unhealthy (UDP), and healthy (HDP). UDP also increased the chance of elevated %HbA1c levels (P = 0.034). T2DM individuals' who presented magnesium deficiency had a higher chance of elevated %HbA1c levels (8.312-fold) and those in the lowest quartile (Q) of the UDP (Q1: P = 0.007; Q2: P = 0.043) had a lower chance of elevated %HbA1c levels. However, the lower quartiles of the HDP were associated with a greater chance of alterations in the %HbA1c level (Q1: P = 0.050; Q2: P = 0.044). No association was observed between MDP and the variables studied. Magnesium deficiency and UDP were associated with a higher chance of inadequate glycemic control in T2DM individuals.

Determination of nutrients in sugarcane juice using slurry sampling and detection by ICP OES.

The fractional factorial and Doehlert designs for optimization of a slurry sampling procedure to determine of nutrients in sugarcane juice by inductively coupled plasma optical emission spectrometry (ICP OES) were applied. External calibration curves were used for direct analysis of the slurry. This procedure allowed determination of Ca, Cu, Fe, K and Mg with limits of detection (LoD) obtained of 2.0, 0.04, 0.2, 1.0 and 1.5 mg L-1, respectively. The precision was expressed as relative standard deviation (%RSD), being better than 1.4% (n = 3). Accuracy was confirmed by comparison with sample digestion method. The results for analysis of fourteen sugarcane juices samples demonstrated that the nutrients Ca, Cu, Fe, K and Mg have average contents of 108, 0.506, 6.40, 470 and 114 mg L-1, respectively. The proposed analytical method is a good alternative for simultaneous determination of nutrients in sugarcane juice using introduction of slurries and detection by ICP OES.