Michelle C Dimitris1, Jennifer A Hutcheon2, Robert W Platt3, Katherine P Himes4, Lisa M Bodnar5, Jay S Kaufman3. 1. Department of Epidemiology, Biostatistics, and Occupational Health, McGill University, Montreal, Quebec, Canada. Electronic address: michelle.dimitris@mail.mcgill.ca. 2. Department of Obstetrics & Gynaecology, University of British Columbia, Vancouver, British Columbia Canada. 3. Department of Epidemiology, Biostatistics, and Occupational Health, McGill University, Montreal, Quebec, Canada. 4. Department of Obstetrics, Gynecology, and Reproductive Sciences, University of Pittsburgh School of Medicine, Pittsburgh, PA. 5. Department of Epidemiology, University of Pittsburgh Graduate School of Public Health, Pittsburgh, PA.
Abstract
PURPOSE: Researchers are interested in studying longitudinal patterns of gestational weight gain, yet this requires daily/weekly weights, and maternal weight is measured only during prenatal visits. We evaluated the relative accuracy and precision of methods for estimating maternal weight gain between prenatal visits among twin and singleton pregnancies. METHODS: We analyzed cohorts of dichorionic twin and singleton pregnancies delivered from 1998-2013 in Pittsburgh, Pennsylvania. We mimicked a typical study by retaining pre-pregnancy, first prenatal visit, glucose screening visit, and delivery weights, using these to fit interpolation models, estimating weight throughout pregnancy using 16 different methods, and calculating the difference in kilograms between predicted and measured values among remaining weights. We evaluated the performance of each model by calculating root mean squared error (RMSE). RESULTS: RMSE ranged from 1.55 to 6.09 kg in twins (n = 2067) and 1.45 to 4.87 kg in singletons (n = 7331). The most accurate and precise methods incorporated restricted cubic splines, random intercepts and slopes for pregnancy, and internal knots demarcating trimesters/quantiles (RMSE = 1.55/1.56 kg in twins, 1.45/1.45 kg in singletons), while individual-level linear interpolation between proximal measurements also performed well. CONCLUSIONS: Accuracy and precision of methods for estimating maternal weight gain between measurements differed by model, and were best among individually-tailored and flexible models.
PURPOSE: Researchers are interested in studying longitudinal patterns of gestational weight gain, yet this requires daily/weekly weights, and maternal weight is measured only during prenatal visits. We evaluated the relative accuracy and precision of methods for estimating maternal weight gain between prenatal visits among twin and singleton pregnancies. METHODS: We analyzed cohorts of dichorionic twin and singleton pregnancies delivered from 1998-2013 in Pittsburgh, Pennsylvania. We mimicked a typical study by retaining pre-pregnancy, first prenatal visit, glucose screening visit, and delivery weights, using these to fit interpolation models, estimating weight throughout pregnancy using 16 different methods, and calculating the difference in kilograms between predicted and measured values among remaining weights. We evaluated the performance of each model by calculating root mean squared error (RMSE). RESULTS: RMSE ranged from 1.55 to 6.09 kg in twins (n = 2067) and 1.45 to 4.87 kg in singletons (n = 7331). The most accurate and precise methods incorporated restricted cubic splines, random intercepts and slopes for pregnancy, and internal knots demarcating trimesters/quantiles (RMSE = 1.55/1.56 kg in twins, 1.45/1.45 kg in singletons), while individual-level linear interpolation between proximal measurements also performed well. CONCLUSIONS: Accuracy and precision of methods for estimating maternal weight gain between measurements differed by model, and were best among individually-tailored and flexible models.
Authors: Lisa M Bodnar; Katherine P Himes; Barbara Abrams; Sara M Parisi; Jennifer A Hutcheon Journal: Pregnancy Hypertens Date: 2018-10-15 Impact factor: 2.899
Authors: Jennifer A Hutcheon; Lisa M Bodnar; K S Joseph; Barbara Abrams; Hyagriv N Simhan; Robert W Platt Journal: Paediatr Perinat Epidemiol Date: 2012-01-16 Impact factor: 3.980
Authors: Lisa M Bodnar; Jennifer A Hutcheon; Sara M Parisi; Sarah J Pugh; Barbara Abrams Journal: Paediatr Perinat Epidemiol Date: 2014-12-10 Impact factor: 3.980
Authors: Jennifer A Hutcheon; Robert W Platt; Barbara Abrams; Betty J Braxter; Cara L Eckhardt; Katherine P Himes; Lisa M Bodnar Journal: Paediatr Perinat Epidemiol Date: 2018-01-29 Impact factor: 3.980
Authors: Jennifer A Hutcheon; Olof Stephansson; Sven Cnattingius; Lisa M Bodnar; Kari Johansson Journal: Epidemiology Date: 2019-03 Impact factor: 4.822