Social and Nutritional Profiles of Pregnant Women: A Cluster Analysis on the "MAMI-MED" Cohort.

BACKGROUND/OBJECTIVES: During the pre-conceptional period, addressing social determinants of health (SDOH) is essential for reducing maternal health disparities, particularly among disadvantaged groups. Key SDOH factors such as income, education, and healthcare access significantly influence maternal and infant outcomes, increasing risks like miscarriage, preterm birth, and pregnancy complications. Here, we aimed to explore maternal and neonatal characteristics according to socio-economic status. Thus, we identified clusters of pregnant women with similar social and behavioral characteristics and explored their variability in terms of neonatal outcomes.

METHODS

Data from 1512 pregnant women in the "MAMI-MED" cohort at ARNAS Garibaldi Nesima in Catania were analyzed. A two-step cluster analysis grouped the women based on education level, employment status, pre-pregnancy nutritional status, and Mediterranean diet score (MDS).

RESULTS

Two clusters of pregnant women were identified. Cluster 1 (n = 739) consisted of women with lower educational attainment who were unemployed, overweight and/or obese, and had a lower mean MDS. Instead, cluster 2 (n = 773) was mostly characterized by women with a medium-high level of education who were employed, had normal weight, and had a higher average MDS. Women in cluster 1 had significantly higher proportions of preterm births ( = 0.004), low-birth weight newborns ( = 0.002), and large-for-gestational-age newborns. Differences in gestational week ( < 0.001), birth weight ( < 0.001), and newborn length ( = 0.004) were also noted between the two clusters.

CONCLUSIONS

Cluster analysis can help identify high-risk groups who may benefit from personalized public health interventions. Our results highlight the need to examine the complex interactions between socio-demographic, behavioral, and genetic factors that contribute to maternal-infant health.