Data-Driven BMI Stratification-Based Determination of Optimal Timing for Non-Invasive Prenatal Testing (NIPT) in Pregnant Women

To optimize the optimal timing for Y-chromosome concentration detection in non-invasive prenatal testing (NIPT) and mitigate maternal BMI ’ s impact on accuracy, this study developed a BMI-grouped differentiated NIPT timing prediction model, with Spearman correlation analysis verifying key variable relationships.Pregnant women were categorized into 6 BMI groups . Y-chromosome concentration across gestational weeks was predicted via a multi-factor integrated timing optimization model. Optimal timing for each group was determined by minimizing total risk, combining "failure risk (weighted by squared false-negative probability)" and "gestational week risk (weighted by exponential growth)". Spearman analysis validated correlations between BMI, Y-chromosome concentration, and optimal timing.The model yielded distinct detection timings: underweight (18.2 weeks), normal-low (18.0 weeks), normal-high (21.7 weeks), overweight (21.6 weeks), obese Class I (21.2 weeks), and obese Class II (19.8 weeks). BMI negatively correlated with Y-chromosome concentration (r=-0.62, P2for concentration prediction was 0.75, with ≥95% success probability at optimal timings. This model enables personalized NIPT timing via BMI grouping and risk balancing. Spearman analysis confirms BMI’s critical role in detection timing, supporting clinical NIPT protocol optimization.