Use of spline regression in an analysis of maternal prepregnancy body mass index and adverse birth outcomes: does it tell us more than we already know?

Abstract

Purpose: Categorical analyses of prepregnancy body mass index (BMI) have shown that maternal overweight and obesity are associated with adverse pregnancy outcomes. It is unclear whether further insight into these associations can be gained from spline regression.

Methods: We used spline regression to examine the relations between prepregnancy BMI and five adverse pregnancy outcomes in the Baltimore-Washington Infant Study, a case-control study of congenital cardiac defects. Analyses included 3,226 singleton live-born control infants delivered 1981 through 1989. We modeled BMI using (a) traditional categories of underweight, average weight, overweight, and obese and (b) restricted quadratic splines.

Results: We confirmed that overweight status and obesity were associated with increased risk of macrosomia and large for gestational age. For these outcomes, splines provided detail about the associations at the ends of the BMI distribution and within the average BMI category. Spline analyses also showed that underweight status was associated with increased risk of preterm delivery.

Conclusions: Analyses of traditional categories of BMI provide good understanding of the associations with several adverse birth outcomes. For three outcomes, modeling with splines provided additional insight regarding dose-response relations within categories. Results suggest the need for further analyses of average BMI and adverse pregnancy outcomes.