Background/Objectives: Insulin resistance during pregnancy is a key factor underlying gestational diabetes mellitus (GDM) and other adverse perinatal outcomes (APOs). While traditional markers, such as HOMA-IR, are used to evaluate insulin resistance, they may be inaccessible in resource-limited settings. The triglyceride–glucose (TyG) index has emerged as a practical alternative. This study aimed to assess whether or not a TyG index > 8.6 during the first trimester of pregnancy is associated with an increased risk of APOs, including GDM, preeclampsia, and other maternal and neonatal complications. Methods: A prospective cohort study was conducted involving 333 pregnant women in Mexico City, divided into two groups: Group 1 (TyG index > 8.6, n = 153) and Group 2 (TyG index ≤ 8.6, n = 180). Primary outcomes included gestational diabetes mellitus (GDM), hypertensive disorders of pregnancy, preeclampsia, preterm birth, cesarean section, and large-for-gestational-age (LGA) and small-for-gestational-age (SGA) neonates. Logistic regression models were used to calculate the adjusted relative risk (aRR) and 95% confidence intervals (CIs), adjusting for maternal age, pregestational weight, and body mass index (BMI). Results: Women with a TyG index > 8.6 had a significantly higher pregestational weight and BMI than those with a TyG index ≤ 8.6. Group 1 demonstrated a higher risk of GDM (RR 2.05; 95% CI: 1.23–3.41) and preeclampsia (RR 2.15; 95% CI: 1.10–4.21). After adjusting for maternal age, pregestational weight, and BMI, these associations remained significant: GDM (aRR 1.87; 95% CI: 1.0–2.5) and preeclampsia (aRR 2.18; 95% CI: 1.1–5.0). No significant associations were found between an elevated TyG index and other APOs, including LGA, SGA, preterm birth, or cesarean delivery. Conclusions: A first-trimester TyG index > 8.6 is significantly associated with an increased risk of GDM and preeclampsia, highlighting its potential as a predictive marker for adverse perinatal outcomes. These findings underscore the utility of the TyG index as a practical, cost-effective tool for early risk stratification, particularly in resource-limited settings. Further multi-center research is needed to validate these results and refine population-specific thresholds.

Obesity is associated with inflammatory changes and accumulation and phenotype polarization of adipose tissue macrophages (ATMs). Obese pregnant women have alterations in adipose tissue composition, but a detailed description of macrophage population is not available. In this study, we characterized macrophage populations in visceral adipose tissue (VAT) from pregnant women with normal, overweight, and obese pregestational weight. Immunophenotyping of macrophages from VAT biopsies was performed by flow cytometry using CD45 and CD14 as markers of hematopoietic and monocyte linage, respectively, while HLA-DR, CD11c, CD163, and CD206 were used as pro- and anti-inflammatory markers. Adipocyte number and size were evaluated by light microscopy. The results show that pregnant women that were overweight and obese during the pregestational period had adipocyte hypertrophy. Two different macrophage populations in VAT were identified: recruited macrophages (CD45+CD14+), and a novel population lacking CD45, which was considered to be a resident macrophages subset (CD45−CD14+). The number of resident HLA−DRlow/− macrophages showed a negative correlation with body mass index (BMI). Both resident and recruited macrophages from obese women expressed higher CD206 levels. CD11c expression was higher in resident HLA-DR+ macrophages from obese women. A strong correlation between CD206 and CD11c markers and BMI was observed. Our findings show that being overweight and obese in the pregestational period is associated with adipocyte hypertrophy and specific ATMs populations in VAT.

Maternal obesity has been related to adverse neonatal outcomes and fetal programming. Oxidative stress and adipokines are potential biomarkers in such pregnancies; thus, the measurement of these molecules has been considered critical. Therefore, we developed artificial neural network (ANN) models based on maternal weight status and clinical data to predict reliable maternal blood concentrations of these biomarkers at the end of pregnancy. Adipokines (adiponectin, leptin, and resistin), and DNA, lipid and protein oxidative markers (8-oxo-2′-deoxyguanosine, malondialdehyde and carbonylated proteins, respectively) were assessed in blood of normal weight, overweight and obese women in the third trimester of pregnancy. A Back-propagation algorithm was used to train ANN models with four input variables (age, pre-gestational body mass index (p-BMI), weight status and gestational age). ANN models were able to accurately predict all biomarkers with regression coefficients greater than R² = 0.945. P-BMI was the most significant variable for estimating adiponectin and carbonylated proteins concentrations (37%), while gestational age was the most relevant variable to predict resistin and malondialdehyde (34%). Age, gestational age and p-BMI had the same significance for leptin values. Finally, for 8-oxo-2′-deoxyguanosine prediction, the most significant variable was age (37%). These models become relevant to improve clinical and nutrition interventions in prenatal care.

Pregnant women with diabetes often present impaired fetal growth, which is less common if maternal diabetes is well-controlled. However, developing strategies to estimate fetal body composition beyond fetal growth that could better predict metabolic complications later in life is essential. This study aimed to evaluate subcutaneous fat tissue (femur and humerus) in fetuses with normal growth among pregnant women with well-controlled diabetes using a reproducible 3D-ultrasound tool and offline TUI (Tomographic Ultrasound Imaging) analysis. Additionally, three artificial intelligence classifier models were trained and validated to assess the clinical utility of the fetal subcutaneous fat measurement. A significantly larger subcutaneous fat area was found in three-femur and two-humerus selected segments of fetuses from women with diabetes compared to the healthy pregnant control group. The full classifier model that includes subcutaneous fat measure, gestational age, fetal weight, fetal abdominal circumference, maternal body mass index, and fetal weight percentile as variables, showed the best performance, with a detection rate of 70%, considering a false positive rate of 10%, and a positive predictive value of 82%. These findings provide valuable insights into the impact of maternal diabetes on fetal subcutaneous fat tissue as a variable independent of fetal growth.

The aim of this study was to examine the efficacy of intensive medical nutrition therapy (MNT) plus metformin in preventing gestational diabetes mellitus (GDM) among high-risk Mexican women. An open-label randomized clinical trial was conducted. Inclusion criteria were pregnant women with three or more GDM risk factors: Latino ethnic group, maternal age >35 years, body mass index >25 kg/m², insulin resistance, and a history of previous GDM, prediabetes, a macrosomic neonate, polycystic ovarian syndrome, or a first-degree relative with type 2 diabetes. Women before 15 weeks of gestation were assigned to group 1 (n = 45): intensive MNT-plus metformin (850 mg twice/day) or group 2 (n = 45): intensive MNT without metformin. Intensive MNT included individual dietary counseling, with ≤50% of total energy from high carbohydrates. The primary outcome was the GDM incidence according to the International Association of Diabetes Pregnancy Study Groups criteria. There were no significant differences in baseline characteristics and adverse perinatal outcomes between the groups. The GDM incidence was n = 11 (24.4%) in the MNT plus metformin group versus n = 7 (15.5%) in the MNT without metformin group: p = 0.42 (RR: 1.57 [95% CI: 0.67–3.68]). There is no benefit in adding metformin to intensive MNT to prevent GDM among high-risk Mexican women. Clinical trials registration: NCT01675310.

Background: Vitamin B12 deficiency, hyperhomocysteinemia, and diabetes are emerging determinants of cardiovascular risk, particularly among women. Early detection and treatment represent an important public health opportunity to reduce the burden of disease and promote health equity. Objective: We aimed to quantify the prevalence of vitamin B12 deficiency, hyperhomocysteinemia, and diabetes, and to evaluate the potential impact of detecting and addressing these conditions on reducing CVD risk in adult Mexican women. Methods: We analyzed data from 1197 women aged 20–49 years from Mexico’s 2022–2023 National Health and Nutrition Survey (ENSANUT). Serum vitamin B12, folate, and homocysteine were quantified, and 10-year CVD risk was estimated using Framingham and Globorisk models. Population-attributable fractions and cost–benefit analyses were used to assess preventable CVD cases and the economic feasibility of nationwide vitamin B12 supplementation. Results: Nationwide, 37.2% of women have vitamin B12 deficiency, and 30.6% have borderline levels. In Southern Mexico, the prevalence of vitamin B12 deficiency is higher, reaching 52.4%. Elevated homocysteine levels were detected in 12.3% of women. The predicted number of preventable CVD cases ranged from 10,000 to 14,000, and the benefit–cost ratio exceeded 1, supporting economic feasibility. Conclusions: Vitamin B12 deficiency and hyperhomocysteinemia are very common among Mexican women and are associated with an increased cardiovascular risk, especially in those aged 40 to 49. The analysis showed that implementing a national vitamin B12 supplementation strategy could be a cost-effective preventive measure, with a benefit–cost ratio ranging from 1.93 in the base case to 2.98 when broader societal savings are taken into account. These findings highlight the potential of targeted nutritional interventions to reduce the burden of cardiovascular disease in women.