Gestational Diabetes Mellitus Subtypes Classified by Oral Glucose Tolerance Test and Maternal and Perinatal Outcomes: Results of a Mexican Multicenter Prospective Cohort Study "Cuido Mi Embarazo".

Purpose: This study explores the impact of gestational diabetes mellitus (GDM) subtypes classified by oral glucose tolerance test (OGTT) values on maternal and perinatal outcomes. Patients and Methods: This multicenter prospective cohort study (May 2019-December 2022) included participants from the Mexican multicenter cohort study Cuido mi Embarazo (CME). Women were classified into four groups per 75-g 2-h OGTT: 1) normal glucose tolerance (normal OGTT), 2) GDM-Sensitivity (isolated abnormal fasting or abnormal fasting in combination with 1-h or 2-h abnormal results), 3) GDM-Secretion (isolated abnormal values at 1-h or 2-h or their combination), and 4) GDM-Mixed (three abnormal values). Cesarean delivery, neonates large for gestational age (LGA), and pre-term birth rates were among the outcomes compared. Between-group comparisons were analyzed using either the t-test, chi-square test, or Fisher's exact test. Results: Of 2,056 Mexican pregnant women in the CME cohort, 294 (14.3%) had GDM; 53.7%, 34.4%, and 11.9% were classified as GDM-Sensitivity, GDM-Secretion, and GDM-Mixed subtypes, respectively. Women with GDM were older (p = 0.0001) and more often multiparous (p = 0.119) vs without GDM. Cesarean delivery (63.3%; p = 0.02) and neonate LGA (10.7%; p = 0.078) were higher in the GDM-Mixed group than the overall GDM group (55.6% and 8.4%, respectively). Pre-term birth was more common in the GDM-Sensitivity group than in the overall GDM group (10.2% vs 8.5%, respectively; p=0.022). At 6 months postpartum, prediabetes was more frequent in the GDM-Sensitivity group than in the overall GDM group (31.6% vs 25.5%). Type 2 diabetes was more common in the GDM-Mixed group than in the overall GDM group (10.0% vs 3.3%). Conclusion: GDM subtypes effectively stratified maternal and perinatal risks. GDM-Mixed subtype increased the risk of cesarean delivery, LGA, and type 2 diabetes postpartum. GDM subtypes may help personalize clinical interventions and optimize maternal and perinatal outcomes.

Trends of Antihypertensive, Antidiabetic, and Nonsteroidal Anti-Inflammatory Drugs Use among the Health Workers Cohort Study, Mexico 2004 to 2018.

Background: Hypertension and type 2 diabetes (T2D) are the most prevalent noncommunicable diseases in Mexico and worldwide. According to international practice management guidelines, the principal chronic management therapy is daily oral medication. Aim: We aim to describe the trends of antihypertensive, antidiabetic, and nonsteroidal anti-inflammatory (NSAID) drugs use among the Mexican adult population from 2004-2018. Methods: We analyzed data from the Health Workers Cohort Study (HWCS) for males and females aged >18 years. We calculated the prevalence of chronic diseases and utilization for every kind of antihypertensive, antidiabetic, and NSAIDs (measured by self-reported utilization) at baseline and two follow-ups (2004, 2010, and 2017). Trends were analyzed using Fisher's exact test. Results: Hypertension prevalence increased from 19.8 to 30.3%, higher than T2D prevalence from 7.0 to 12.8% through fourteen years of follow-up. Like the self-reported dual therapy, the proportion of patients using beta-blockers and angiotensin II receptor blockers increased. Regarding T2D, the prevalence of metformin utilization increased to 83.9%. The utilization of common NSAIDs, mainly for muscular pain, remained around 13 to 16%. Conclusions: Our findings showed a changing prevalence of drug utilization for hypertension and T2D between 2004 and 2018 and consistent use of NSAIDs in the adult Mexican population.

Sex differences in the influence of type 2 diabetes (T2D)-related genes, parental history of T2D, and obesity on T2D development: a case-control study.

BACKGROUND: This study investigated the effect of sex and age at type 2 diabetes (T2D) diagnosis on the influence of T2D-related genes, parental history of T2D, and obesity on T2D development. METHODS: In this case-control study, 1012 T2D cases and 1008 healthy subjects were selected from the Diabetes in Mexico Study database. Participants were stratified by sex and age at T2D diagnosis (early, ≤ 45 years; late, ≥ 46 years). Sixty-nine T2D-associated single nucleotide polymorphisms were explored and the percentage contribution (R2) of T2D-related genes, parental history of T2D, and obesity (body mass index [BMI] and waist-hip ratio [WHR]) on T2D development was calculated using univariate and multivariate logistic regression models. RESULTS: T2D-related genes influenced T2D development most in males who were diagnosed early (R2 = 23.5%; females, R2 = 13.5%; males and females diagnosed late, R2 = 11.9% and R2 = 7.3%, respectively). With an early diagnosis, insulin production-related genes were more influential in males (76.0% of R2) while peripheral insulin resistance-associated genes were more influential in females (52.3% of R2). With a late diagnosis, insulin production-related genes from chromosome region 11p15.5 notably influenced males while peripheral insulin resistance and genes associated with inflammation and other processes notably influenced females. Influence of parental history was higher among those diagnosed early (males, 19.9%; females, 17.5%) versus late (males, 6.4%; females, 5,3%). Unilateral maternal T2D history was more influential than paternal T2D history. BMI influenced T2D development for all, while WHR exclusively influenced males. CONCLUSIONS: The influence of T2D-related genes, maternal T2D history, and fat distribution on T2D development was greater in males than females.

The prevalence of diabetes worldwide is slightly higher in men than in women, particularly in those aged 50 or younger (16.5% for men versus 13.5% for women). This suggests that hormonal differences could be critical in early development of Type 2 diabetes. Some known factors previously associated with T2D, such as genes, parental history of diabetes and obesity, could have a differential influence between both sexes for the development of T2D. We compared these factors between 1008 healthy individual and 1012 TD2 patients. In this comparison, we calculated the percentage of variability of the disease explained by each factor. As expected, the most noticeable differences between men and women were observed in T2D diagnoses before age 46. Genes had a greater effect in men than in women (23.5% vs. 13.5%). While genes involved in insulin production have a greater influence on men, genes involved in peripheric insulin resistance have a greater influence on women. The overall parental history of T2D influences similarly in males (19.9%) and females (17.5%), however, the unilateral genetic influence of the mother was much greater in males than in females. The influence of global and abdominal obesity played a greater role in men than in women. In T2D diagnoses after age of 45, the influence of genes and parental history of diabetes decreases markedly, and the relative influence of global obesity augments. However, while genes linked to insulin resistance and inflammation predominate in females, genes linked to insulin secretion predominate in males.

Development and validation of a multivariable genotype-informed gestational diabetes prediction algorithm for clinical use in the Mexican population: insights into susceptibility mechanisms.

INTRODUCTION: Gestational diabetes mellitus (GDM) is underdiagnosed in Mexico. Early GDM risk stratification through prediction modeling is expected to improve preventative care. We developed a GDM risk assessment model that integrates both genetic and clinical variables. RESEARCH DESIGN AND METHODS: Data from pregnant Mexican women enrolled in the 'Cuido mi Embarazo' (CME) cohort were used for development (107 cases, 469 controls) and data from the 'Mónica Pretelini Sáenz' Maternal Perinatal Hospital (HMPMPS) cohort were used for external validation (32 cases, 199 controls). A 2-hour oral glucose tolerance test (OGTT) with 75 g glucose performed at 24-28 gestational weeks was used to diagnose GDM. A total of 114 single-nucleotide polymorphisms (SNPs) with reported predictive power were selected for evaluation. Blood samples collected during the OGTT were used for SNP analysis. The CME cohort was randomly divided into training (70% of the cohort) and testing datasets (30% of the cohort). The training dataset was divided into 10 groups, 9 to build the predictive model and 1 for validation. The model was further validated using the testing dataset and the HMPMPS cohort. RESULTS: Nineteen attributes (14 SNPs and 5 clinical variables) were significantly associated with the outcome; 11 SNPs and 4 clinical variables were included in the GDM prediction regression model and applied to the training dataset. The algorithm was highly predictive, with an area under the curve (AUC) of 0.7507, 79% sensitivity, and 71% specificity and adequately powered to discriminate between cases and controls. On further validation, the training dataset and HMPMPS cohort had AUCs of 0.8256 and 0.8001, respectively. CONCLUSIONS: We developed a predictive model using both genetic and clinical factors to identify Mexican women at risk of developing GDM. These findings may contribute to a greater understanding of metabolic functions that underlie elevated GDM risk and support personalized patient recommendations.

MIDO GDM: an innovative artificial intelligence-based prediction model for the development of gestational diabetes in Mexican women.

Given the barriers to early detection of gestational diabetes mellitus (GDM), this study aimed to develop an artificial intelligence (AI)-based prediction model for GDM in pregnant Mexican women. Data were retrieved from 1709 pregnant women who participated in the multicenter prospective cohort study 'Cuido mi embarazo'. A machine-learning-driven method was used to select the best predictive variables for GDM risk: age, family history of type 2 diabetes, previous diagnosis of hypertension, pregestational body mass index, gestational week, parity, birth weight of last child, and random capillary glucose. An artificial neural network approach was then used to build the model, which achieved a high level of accuracy (70.3%) and sensitivity (83.3%) for identifying women at high risk of developing GDM. This AI-based model will be applied throughout Mexico to improve the timing and quality of GDM interventions. Given the ease of obtaining the model variables, this model is expected to be clinically strategic, allowing prioritization of preventative treatment and promising a paradigm shift in prevention and primary healthcare during pregnancy. This AI model uses variables that are easily collected to identify pregnant women at risk of developing GDM with a high level of accuracy and precision.

Diagnostic Accuracy of Capillary Blood Glucometer Testing for Gestational Diabetes.

Purpose: Few pregnant women in low-resource settings are screened for gestational diabetes mellitus (GDM) using the gold standard oral glucose tolerance test (OGTT). This study compared capillary blood glucose testing with 2-h plasma glucose measurements obtained using the 75-g OGTT to screen for GDM at primary healthcare clinics in Mexico. Patients and Methods: Pregnant women who participated in a previous prospective multicenter longitudinal cohort study and who had not been previously diagnosed with diabetes were included. Participants were evaluated using the plasmatic 2-h 75-g OGTT with simultaneous capillary blood glucose measurements using a glucometer. The study endpoint was the comparability of the glucometer results to the gold standard OGTT when collected simultaneously. Sensitivity, specificity, and area under the curve of the glucose measurements obtained for capillary blood compared with venous plasma (gold standard) were calculated to determine diagnostic accuracy. Results: The study included 947 pregnant women who had simultaneous glucose measurements available (blood capillary [glucometer] and venous blood OGTT). Overall, capillary blood glucose testing was very sensitive (89.47%); the specificity was 66.58% and the area under the curve (95% confidence interval) was 0.78 (0.74-0.81). The sensitivity, specificity and area under the curve of each capillary measurement were: 89.47%, 66.58% and 0.78 (0.74-0.82) for the fasting measurement, 91.53%, 93.24% and 0.92 (0.88-0.96) for the one-hour measurement, and 89.80%, 93.32%, 0.91 (0.87-0.95) for the second-hour measurement, respectively. No adverse events were reported. Conclusion: Capillary OGTT is a valid alternative to the gold standard OGTT for screening of GDM in low-resource situations or in situations where there are other limitations to performing the OGTT as part of primary healthcare services.

Self-perceived stress is associated with adiposity and atherosclerosis. The GEA Study.

BACKGROUND: A growing body of evidence suggests that psychological stress is an independent cardiovascular risk factor. Obesity prevalence shows accelerating trends worldwide, and is known to be associated with a range of comorbidities and survival. The aim of this study was to assess the relationship between self-perceived psychological stress with parameters of adiposity, metabolic syndrome, and subclinical atherosclerosis in Mexican participants. METHODS: Metabolic Syndrome was defined using the Adult Treatment Panel III criteria, obesity was defined as BMI >30, subclinical atherosclerosis disease was determined by computed tomography, and carotid intima media thickness was determined by ultrasonography. Self-perceived psychological stress was assessed using a single-item questionnaire. RESULTS: A total of 1243 control subjects were included in the sample, mean age 54.2 ± 9 years old; the prevalence of chronic self-perceived psychological stress (>5 years) was 10.13 %, female gender (62.7 %), obesity prevalence (48.4 %), and self-reporting sedentary lifestyle (56.3 %). The chronic stressed cohort presented higher subcutaneous abdominal fat content (285 vs 319 cm(2)), and carotid intima media thickness (0.63 vs 0.66 mm; p < 0.01 for both). However, after adjustment for lifestyle/social covariates (Model 1) and biological mediators (Model 2), chronic self-perceived stress was independently associated with obesity in men (OR 2.85, 95 % CI 1.51 - 5.40) and carotid atherosclerosis in women (OR 2.262, 95 % CI 1.47 - 4.67; p < 0.01 for both). CONCLUSION: Our study suggests that self-reported chronic stress is an independent risk factor for obesity in men. In addition, carotid atherosclerosis was also found to be an independent risk factor in women in a Mexican population sample.