RESUMO
BACKGROUND: The impacts of prenatal maternal affective symptoms on the placental structure are not well-established. Employing Geographic Information System (GIS) spatial autocorrelation, Moran's I, can help characterize placental thickness uniformity/variability and evaluate the impacts of maternal distress on placental topography. METHODS: This study (N = 126) utilized cohort data on prenatal maternal affective symptoms and placental 2D and 3D morphology. Prenatal maternal depression, stress, anxiety and sleep quality were scored for each trimester using the Edinburgh Postnatal Depression Scale (EPDS), Stressful Life Event Scale (SLE), Penn State Worry Questionnaire (PSWQ), and Pittsburgh Sleep Quality Index (PSQI), respectively. Placental shape was divided into Voronoi cells and thickness variability among these cells was computed using Moran's I for 4-nearest neighbors and neighbors within a 10 cm radius. Sex-stratified Spearman correlations and linear regression were used to study associations between mean placental thickness, placental GIS variables, placental weight and the average score of each maternal variable. RESULTS: For mothers carrying boys, poor sleep was associated with higher mean thickness (r = 0.308,p = 0.035) and lower placental thickness uniformity (r = -0.36,p = 0.012). Lower placental weight (r = 0.395,p = 0.003), higher maternal depression (r = -0.318,p = 0.019) and worry/anxiety (r = -0.362,p = 0.007) were associated with lower placental thickness uniformity for mothers carrying girls. LIMITATIONS: The study is exploratory and not all GIS models were developed. Excluding high-risk pregnancies prevented investigating pregnancy complications related hypotheses. A larger sample size is needed for greater confidence for clinical application. CONCLUSIONS: Placental topography can be studied using GIS theory and has shown that prenatal maternal affective symptoms and sleep have sex-specific associations with placental thickness.
