Impact of Maternal Micronutrient Intake on Gestational Diabetes Risk: Results from Greece's BORN2020 Prospective Cohort Study.

Understanding how maternal micronutrient intake and dietary habits impact gestational diabetes mellitus (GDM) is crucial. Data from 797 pregnant women were prospectively analyzed to assess GDM status with the oral glucose tolerance test (OGTT). Nutritional intake was evaluated using a validated food frequency questionnaire (FFQ) across two periods: Period A, covering 6 months before pregnancy, and Period B, from pregnancy onset to mid-gestation (24 weeks). Micronutrient intakes were compared against the European Food Safety Authority (EFSA) dietary reference values (DRVs) and were used to estimate the mean adequacy ratio (MAR) to assess dietary adequacy. GDM was diagnosed in 14.7% (n = 117) of women with the characteristics of a higher mean maternal age (MA) and pre-pregnancy body mass index (BMI). Out of the 13 vitamins assessed, biotin, folate, niacin, and pantothenic acid were found significantly higher in the GDM group, as did iron, magnesium, manganese, phosphorus, and zinc from the 10 minerals. The results were influenced by the timing of the assessment. Importantly, MAR was higher during pregnancy and was found to increase the risk of GDM by 1% (95%CI: 1, 1.02). A sensitivity analysis revealed that reducing MAR significantly raised the GDM risk by 68% (95%CI: 1.02, 2.79). No association was revealed between adherence to the Mediterranean diet (MD) and GDM risk. These findings highlight areas for further investigation into whether dietary modifications involving these specific micronutrients could effectively influence GDM outcomes.

Preconceptional micronutrient adequacy among women in Greece: a prospective epidemiological study.

INTRODUCTION: The importance of micronutrient intake during the preconceptional and early pregnancy period for both maternal and fetal outcomes is well-known, however, relevant data are not available for Greek pregnant women. The aim of the present study is to delineate the nutritional status preceding conception among a representative cohort of Greek pregnant women. METHODS: This was a prospective study of pregnant women from routine care, recruited at 11+0-13+6 gestational weeks, between December 2020 and October 2022, at the 3rd Department of Obstetrics and Gynecology, Aristotle University of Thessaloniki, Greece. Eligible participants for the study included healthy pregnant women aged 20 years or older, possessing a proficient understanding of the Greek language, and not engaged in specific nutritional programs. A validated Food Frequency Questionnaire was applied to gather information regarding nutritional habits in the last 6 months prior to conception. The consumption of nutrients was compared to the reference intake levels suggested by the European Food Safety Authority. Further analyses between different participants' subgroups were performed. RESULTS: Overall, 1100 pregnant women (mean age: 32.4 ± 4.9 years) were enrolled. Almost all examined micronutrients' intake was significantly different from dietary reference values. Furthermore, nutrient adequacy ratio was below 60% in 6 out of 22 micronutrients examined, and Mean Adequacy Ratio was 93%. However, Mean Adequacy Ratio is characterized by extreme variance between the examined values. Iodine, folic acid, potassium, and vitamin D intake levels were significantly lower than the recommended intake levels (p < .001 for all), while vitamin K and niacin (p < .001 for both) were consumed in great extent. Sodium median intake, without calculating extra salt addition also exceeded the reference value levels (p = .03). Notably, magnesium intake exceeded the upper safety limits in 12.4% of the sample. CONCLUSION: Potential inadequacies in important micronutrients for uneventful pregnancy outcomes have been revealed.. Special attention is needed for magnesium to balance possible toxicity with evident benefits.

Pre-Pregnancy Adherence to Mediterranean Diet and Risk of Gestational Diabetes Mellitus: A Prospective Cohort Study in Greece.

Gestational Diabetes Mellitus (GDM) is a growing epidemic affecting pregnant women and their offspring. This study aimed to identify the relationship between adherence to a Mediterranean diet (MD) before conception and the risk of GDM in a contemporary Greek pregnant cohort. A prospective cohort of pregnant women was recruited at the routine first trimester visit. Nutritional intake was evaluated using a population specific validated food frequency questionnaire (FFQ). Pre-pregnancy adherence to MD was derived using two different scoring systems, the Mediterranean diet index score (MDS), and a modified version. Adjusted odds ratios (aOR) were computed using multiple logistic regression models for each score derived. Of 743 participating women, 112 (15.1%) developed GDM. The MDS index showed that scoring 5-9 points (high adherence) was associated with a lower GDM incidence (aOR: 0.57 95% CI (0.32, 0.90), p = 0.02), while the modified MDS index showed no significant association for any level of adherence. Pre-pregnancy consumption of "meat and derivatives" and "fatty meat and processed meat" was associated with a higher risk of GDM, with both scoring systems (p = 0.008, p = 0.004, respectively). A higher adherence to a MD pre-pregnancy, especially with less meat consumption, may have a protective effect on the occurrence of GDM.

Effect of Gestational Weight Gain during the First Half of Pregnancy on the Incidence of GDM, Results from a Pregnant Cohort in Northern Greece.

The aim of this study was to evaluate the effect of gestational weight gain (GWG) up to 23+6 weeks of gestation on the incidence of Gestational Diabetes Mellitus (GDM). A pregnant cohort of 5948 women in Northern Greece was recruited. Anthropometric features before and during pregnancy were recorded, the GWG by 23+6 weeks was calculated and a Generalized Linear Regression Model (GLM) with subgroup analyses based on weight status were computed. GDM was diagnosed in 5.5% of women. GLM results showed that GDM likelihood increased with maternal age (MA) and pre-pregnancy BMI (aOR: 1.08, 95%CI: [1.06, 1.11] and aOR: 1.09, 95%CI: [1.09, 1.11], respectively). Ιn the normal pre-pregnancy weight group, when the extra weight gain was >8 kgs, the odds of GDM increased (OR: 2.13, 95%CI: [0.98, 4.21], p = 0.03). Women with pre-pregnancy level 2 clinical obesity (OB2 pre) (BMI > 35 and <40 kg/m2) that shifted to OB3 category (BMI ≥ 40 kg/m2) had an increased GDM likelihood (OR: 4.85, 95%CI: [1.50, 15.95]). Women of higher MA may require stricter monitoring for GDM from early pregnancy, while in obese women, recommended GWG may need to be re-evaluated, since refraining from any weight gain may have a preventive effect for GDM.

Prediction of Gestational Diabetes Mellitus in the First Trimester of Pregnancy Based on Maternal Variables and Pregnancy Biomarkers.

Gestational diabetes mellitus (GDM) is a significant health concern with adverse outcomes for both pregnant women and their offspring. Recognizing the need for early intervention, this study aimed to develop an early prediction model for GDM risk assessment during the first trimester. Utilizing a prospective cohort of 4917 pregnant women from the Third Department of Obstetrics and Gynecology, Aristotle University of Thessaloniki, Greece, the study sought to combine maternal characteristics, obstetric and medical history, and early pregnancy-specific biomarker concentrations into a predictive tool. The primary objective was to create a series of predictive models that could accurately identify women at high risk for developing GDM, thereby facilitating early and targeted interventions. To this end, maternal age, body mass index (BMI), obstetric and medical history, and biomarker concentrations were analyzed and incorporated into five distinct prediction models. The study's findings revealed that the models varied in effectiveness, with the most comprehensive model combining maternal characteristics, obstetric and medical history, and biomarkers showing the highest potential for early GDM prediction. The current research provides a foundation for future studies to refine and expand upon the predictive models, aiming for even earlier and more accurate detection methods.