Quantitative Analysis of Factors Affecting Fetal Cell-Free DNA Concentration Based on Linear Mixed-Effects Models

This study aims to systematically analyze the independent and combined effects of gestational age and maternal body mass index on fetal Y chromosome concentration, with particular attention to the statistical challenges posed by the prevalence of repeated measurements in the data. To address the non-independence of data resulting from multiple measurements within individuals, this study innovatively employs a linear mixed-effects model as its core analytical framework. Following rigorous data preprocessing, the model specifically incorporates random intercepts to account for individual variability, enabling unbiased estimation of the fixed effects of gestational age and BMI. This approach effectively overcomes the limitation of traditional linear regression, which may underestimate standard errors, ensuring the accuracy of statistical inference. Model analysis reveals a significant upward trend in fetal Y chromosome concentration with advancing gestational age, while maternal BMI exerts a clear negative influence. Significance tests confirm the robustness of these effects. Crucially, the model variance decomposition identifies substantial between-subject variation, highlighting the necessity and importance of accounting for random effects in analyzing such data. To assess the reliability of conclusions, an in-depth robustness analysis was conducted. After log-transforming the response variable and refitting the model, the direction and statistical significance of key independent variables remained consistent, indicating that the primary findings are not overly constrained by specific model assumptions and exhibit high robustness.