The Influence of Preeclampsia, Advanced Maternal Age and Maternal Obesity in Neonatal Outcomes Among Women with Gestational Diabetes

Clustering of health risk behaviors in pregnant individuals: Data from the Brazilian risk factor surveillance system for non-communicable chronic diseases

OBJECTIVE

To investigate the clustering of health risk behaviors (HRB) and its association with demographics, physical exercise, overweight, perception of health, and diseases in Brazilian pregnant people.

STUDY DESIGN

This is a cross-sectional study using data from the Risk Factor Surveillance System for Non-communicable Chronic Diseases by Telephone Survey (VIGITEL), the main health survey in Brazil.

METHODS

We used data on fruit and vegetable consumption, TV time, tobacco, and alcohol abuse in individuals who reported being pregnant (n = 4553). We used latent class analysis to identify optimal HRB clustering among participants. Multinomial regression (odds ratio [OR] and 95% confidence intervals [95%CI]) was applied to identify factors associated with HRB cluster.

RESULTS

Three clustering classes were identified: "without HRB cluster" (i.e., least unhealthy behaviors) (n = 2402, 52,8%), "moderate HRB cluster" (n = 1983, 43,5%), and "high HRB cluster" (i.e., most unhealthy behaviors) (n = 168, 3,7%). Pregnant people aged 35-50 years (OR = 1.89, 95%CI = 1.01; 3.52) who did not practice physical exercise (OR = 1.94, 95%CI 1.11; 3.39) were more likely to be classified as "high HRB cluster". Participants with 9-11 years (OR = 0.11, 95%CI = 0.07; 0.17) and ≥ 12 (OR = 0.05, 95%CI = 0.02; 0.11) years of education had a lower likelihood of being in the "high HRB cluster".

CONCLUSION

Three HRB clustering patterns were found in this study. Greater maternal age, low education, and absence of physical exercises increased the chances of being in the high HRB cluster group. Participants with higher educational levels were less likely to be in the High HRB cluster.

Refining the diagnosis of gestational diabetes mellitus: a systematic review and meta-analysis

BACKGROUND

Perinatal outcomes vary for women with gestational diabetes mellitus (GDM). The precise factors beyond glycemic status that may refine GDM diagnosis remain unclear. We conducted a systematic review and meta-analysis of potential precision markers for GDM.

METHODS

Systematic literature searches were performed in PubMed and EMBASE from inception to March 2022 for studies comparing perinatal outcomes among women with GDM. We searched for precision markers in the following categories: maternal anthropometrics, clinical/sociocultural factors, non-glycemic biochemical markers, genetics/genomics or other -omics, and fetal biometry. We conducted post-hoc meta-analyses of a subset of studies with data on the association of maternal body mass index (BMI, kg/m2) with offspring macrosomia or large-for-gestational age (LGA).

RESULTS

A total of 5905 titles/abstracts were screened, 775 full-texts reviewed, and 137 studies synthesized. Maternal anthropometrics were the most frequent risk marker. Meta-analysis demonstrated that women with GDM and overweight/obesity vs. GDM with normal range BMI are at higher risk of offspring macrosomia (13 studies [n = 28,763]; odds ratio [OR] 2.65; 95% Confidence Interval [CI] 1.91, 3.68), and LGA (10 studies [n = 20,070]; OR 2.23; 95% CI 2.00, 2.49). Lipids and insulin resistance/secretion indices were the most studied non-glycemic biochemical markers, with increased triglycerides and insulin resistance generally associated with greater risk of offspring macrosomia or LGA. Studies evaluating other markers had inconsistent findings as to whether they could be used as precision markers.

CONCLUSIONS

Maternal overweight/obesity is associated with greater risk of offspring macrosomia or LGA in women with GDM. Pregnancy insulin resistance or hypertriglyceridemia may be useful in GDM risk stratification. Future studies examining non-glycemic biochemical, genetic, other -omic, or sociocultural precision markers among women with GDM are warranted.

Gestational Diabetes Mellitus and Preeclampsia: Correlation and Influencing Factors

Gestational diabetes mellitus (GDM) and preeclampsia (PE) are common pregnancy complications with similar risk factors and pathophysiological changes. Evidence from previous studies suggests that the incidence of PE is significantly increased in women with GDM, but whether GDM is independently related to the occurrence of PE has remained controversial. GDM complicated by PE further increases perinatal adverse events with greater impact on the future maternal and offspring health. Identify factors associated with PE in women with GDM women, specifically those that are controllable, is important for improving pregnancy outcomes. This paper provides the findings of a review on the correlation between GDM and PE, factors associated with PE in women with GDM, possible mechanisms, and predictive markers. Most studies concluded that GDM is independently associated with PE in singleton pregnancy, and optimizing the treatment and management of GDM can reduce the incidence of PE, which is very helpful to improve pregnancy outcomes.