Maternal diet quality and associations with plasma lipid profiles and pregnancy-related cardiometabolic health

Food Insecurity Is Associated with Diet Quality in Pregnancy: A Cross-Sectional Study

Household food insecurity (HFI) and poorer prenatal diet quality are both associated with adverse perinatal outcomes. However, research assessing the relationship between HFI and diet quality in pregnancy is limited. A cross-sectional online survey was conducted to examine the relationship between HFI and diet quality among 1540 pregnant women in Australia. Multiple linear regression models were used to examine the associations between HFI severity (marginal, low, and very low food security compared to high food security) and diet quality and variety, adjusting for age, education, equivalised household income, and relationship status. Logistic regression models were used to assess the associations between HFI and the odds of meeting fruit and vegetable recommendations, adjusting for education. Marginal, low, and very low food security were associated with poorer prenatal diet quality (adj β = -1.9, -3.6, and -5.3, respectively; p < 0.05), and very low food security was associated with a lower dietary variety (adj β = -0.5, p < 0.001). An association was also observed between HFI and lower odds of meeting fruit (adjusted odds ratio [AOR]: 0.61, 95% CI: 0.49-0.76, p < 0.001) and vegetable (AOR: 0.40, 95% CI: 0.19-0.84, p = 0.016) recommendations. Future research should seek to understand what policy and service system changes are required to reduce diet-related disparities in pregnancy.

Associations between diet quality and dietary patterns and gestational diabetes mellitus in a low-risk cohort of pregnant women in Australia: a cross-sectional study

INTRODUCTION

Evidence of associations between the Mediterranean Diet Score (MDS) and Dietary Approaches to Stop Hypertension (DASH) score and gestational diabetes mellitus (GDM) in pregnant women is limited. This study examined changes in MDS and DASH and dietary patterns in Australian pregnant women between early and late pregnancy and their associations with GDM.

METHODS

The data from n = 284 participants were analysed. Diet quality indices and empirical dietary patterns were determined in early (15 ± 3 weeks gestation) and late pregnancy (35 ± 2 weeks gestation). Paired t-tests were used to examine changes in scores for diet quality indices and dietary patterns from early to late pregnancy. Logistic regression analysis was used to examine associations between GDM, diet quality indices and dietary patterns.

RESULTS

Three major dietary patterns were identified at early pregnancy. The first and second dietary patterns included unhealthier and healthier food groups, respectively, and the third comprised mixed food groups. Although diet quality scores did not change over time, consumption of the first dietary pattern increased (p = 0.01), and consumption of the second dietary pattern decreased by late pregnancy in women without GDM (p < 0.001).

CONCLUSION

No associations between DASH score, MDS and GDM were found; however an inverse association was observed between the first dietary pattern and GDM in late pregnancy (p = 0.023). Longitudinal studies are needed to examine diet quality and dietary patterns at early and late pregnancy to inform the development of tailored dietary advice for GDM.

Gestational and Developmental Contributors of Pediatric MASLD

Pediatric metabolic dysfunction-associated steatotic liver disease (MASLD) is common and can be seen as early as in utero. A growing body of literature suggests that gestational and early life exposures modify the risk of MASLD development in children. These include maternal risk factors, such as poor cardiometabolic health (e.g., obesity, gestational diabetes, rapid weight gain during pregnancy, and MASLD), as well as periconceptional dietary exposures, degree of physical activity, intestinal microbiome, and smoking. Paternal factors, such as diet and obesity, also appear to play a role. Beyond gestation, early life dietary exposures, as well as the rate of infant weight gain, may further modify the risk of future MASLD development. The mechanisms linking parental health and environmental exposures to pediatric MASLD are complex and not entirely understood. In conclusion, investigating gestational and developmental contributors to MASLD is critical and may identify future interventional targets for disease prevention.