622Low Birthweight Prediction is Not Improved by Repeated Measures of Gestational Weight: the BOSHI Study

Abstract Background Both pre-pregnancy body mass index and total weight gain during pregnancy are known risk factors for perinatal outcomes. However, little is known if repeated measurements of gestational weight gain can be utilized in the prediction of perinatal outcomes. We examined whether repeated measures of gestational weight improve the prediction of low infant birthweight. Methods Using data from the BOSHI study, we developed prediction models with low infant birthweight (<2500 g) as the outcome and gestational weight gain as the exposure of interest. A prediction model (Model 1) using only baseline values (pre-pregnancy body mass index) as the exposure was compared with a model using baseline and the last weight measurement (Model 2) and a model using baseline and trimester-specific measurements (Model 3). Model performance was assessed using c-statistics, Brier scores, and calibration plots. Results Among women who experienced full-term deliveries and had measured weights, the proportion of low infant birthweights was 5%. The c-statistics of Model 1, Model 2, and Model 3 were 0.78, 0.81, and 0.83, respectively. Other assessments were relatively unchanged. The extent of predictive performance improvement depends not only on the exposure-outcome associations but correlations among exposure measurements. Conclusions The inclusion of repeated gestational weight measurements in a model for predicting low infant birthweight only produced a marginal improvement in predictive performance. Key messages The prediction of low infant birthweight is not substantially improved by using repeated measurements of gestational weight.