Published in:
Open Access 01-12-2020 | Research article
Association of provider advice and gestational weight gain in twin pregnancies: a cross-sectional electronic survey
Published in: BMC Pregnancy and Childbirth | Issue 1/2020
Login to get accessAbstract
Background
Little is known about patient-provider communication on gestational weight gain among women pregnant with twins, a growing population at high risk for adverse maternal and neonatal outcomes. We examined if women’s report of provider advice on gestational weight gain was consistent with the Institute of Medicine (IOM) weight gain guidelines for twin pregnancies, and the association of provider advice on weight gain with women’s weight gain during their twin pregnancy.
Methods
We conducted a cross-sectional survey of 276 women who delivered twins and received prenatal care in the United States. The 2009 IOM provisional weight gain guidelines for twin pregnancies defined whether provider advice on weight gain and women’s weight gain were below, within, or above guidelines. Multinomial logistic regression examined associations between provider advice on weight gain with women’s weight gain, after adjustment for maternal age, gestational age at delivery, education, parity, twin type, use of assisted reproductive technologies and pre-pregnancy BMI category.
Results
Approximately 30% of women described provider advice on weight gain below the IOM guidelines, 60% within, and 10% above guidelines. Compared to women who reported weight gain advice within guidelines, women who reported advice below guidelines or who reported no advice were 7.1 (95% CI: 3.2, 16.0) and 2.7 (95% CI: 1.3, 5.6) times more likely to gain less than recommended, respectively. Women who reported provider advice above guidelines were 4.6 (95% CI: 1.5, 14.2) times more likely to exceed guidelines.
Conclusions
Provider advice on gestational weight gain may be an important predictor of women’s weight gain during twin pregnancies, highlighting the critical need for accurate provider counseling to optimize health outcomes.