This project investigates how maternal stress volatility during pregnancy impacts child health outcomes, using ecological momentary assessments (EMA) to capture daily stress levels across different pregnancy stages. Through analyzing maternal stress data alongside infant health indicators like birth weight, body fat percentage, and telomere length, this study seeks to quantify the relationship between fluctuating prenatal stress and potential newborn health risks.
Ecological Momentary Assessments (EMA): Utilized EMA to capture real-time maternal stress data, providing detailed stress variability across pregnancy trimesters.
Predictor Variables and Clinical Outcomes: Examined predictors such as maternal age, BMI, and obstetric risk, focusing on infant health metrics (e.g., body fat, birth weight).
RMSSD as a Volatility Measure: Employed Root Mean Square of Successive Differences (RMSSD) to quantify stress fluctuations, allowing for a nuanced analysis of stress variability.
Linear Modeling and Analysis: Used refined linear models to assess the impact of stress volatility on newborn health, factoring in maternal demographics and biological traits.
Visual and Statistical Insights: Included visualizations and statistical corrections (e.g., Bonferroni correction) to control for error rates and support reliable conclusions.