TY - JOUR
T1 - Maternal antenatal body mass index gains as predictors of large-for-gestational-age infants and cesarean deliveries in Japanese singleton pregnancies
AU - Takimoto, Hidemi
AU - Sugiyama, Takashi
AU - Nozue, Miho
AU - Kusama, Kaoru
AU - Fukuoka, Hideoki
AU - Kato, Noriko
AU - Yoshiike, Nobuo
PY - 2011/6
Y1 - 2011/6
N2 - Aim: Greater antenatal weight or body mass index (BMI) gains may lead to larger fetuses and thus increase the risk for operative deliveries, such as cesarean deliveries. In order to examine the effect of weekly maternal weight and BMI changes on large-for-gestational-age (LGA) infants and cesarean delivery, delivery records from overall healthy women were analyzed. Materials and Methods: Singleton, term delivery records from January to December 2003, at three obstetric departments (urban, suburban, rural) in Japan (1617 records) were analyzed. Multivariate logistic regression analyses were applied in order to estimate the effect of maternal pre-pregnancy body size, higher maternal weight or BMI gains by calculating the odds ratios for LGA infants and cesarean deliveries. Results: Maternal pre-pregnancy overweight, primiparity, and BMI gains of more than 0.13 per week were independent factors positively related to LGA, and maternal underweight was negatively related. Urban hospital setting, maternal age 35 years or older, primiparity, and BMI gains of more than 0.13 per week independently increased the odds ratios for cesarean delivery. Weight or BMI gains between two-week intervals (26-28 weeks, 32-34 weeks) were not useful for predicting either LGA or cesarean delivery. LGA was unrelated to cesarean delivery risk. Conclusions: Applying BMI gains per week enables target weight gains to be set according to the mother's height, which may be useful in reducing risks for LGA and cesarean delivery, especially in shorter women. Further investigation may be needed to explore the practicality and effectiveness of advising women to gain weight according to their body height.
AB - Aim: Greater antenatal weight or body mass index (BMI) gains may lead to larger fetuses and thus increase the risk for operative deliveries, such as cesarean deliveries. In order to examine the effect of weekly maternal weight and BMI changes on large-for-gestational-age (LGA) infants and cesarean delivery, delivery records from overall healthy women were analyzed. Materials and Methods: Singleton, term delivery records from January to December 2003, at three obstetric departments (urban, suburban, rural) in Japan (1617 records) were analyzed. Multivariate logistic regression analyses were applied in order to estimate the effect of maternal pre-pregnancy body size, higher maternal weight or BMI gains by calculating the odds ratios for LGA infants and cesarean deliveries. Results: Maternal pre-pregnancy overweight, primiparity, and BMI gains of more than 0.13 per week were independent factors positively related to LGA, and maternal underweight was negatively related. Urban hospital setting, maternal age 35 years or older, primiparity, and BMI gains of more than 0.13 per week independently increased the odds ratios for cesarean delivery. Weight or BMI gains between two-week intervals (26-28 weeks, 32-34 weeks) were not useful for predicting either LGA or cesarean delivery. LGA was unrelated to cesarean delivery risk. Conclusions: Applying BMI gains per week enables target weight gains to be set according to the mother's height, which may be useful in reducing risks for LGA and cesarean delivery, especially in shorter women. Further investigation may be needed to explore the practicality and effectiveness of advising women to gain weight according to their body height.
KW - Body mass index
KW - Cesarean delivery
KW - Large-for-gestational-age
KW - Pregnancy
KW - Weight gain
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U2 - 10.1111/j.1447-0756.2010.01396.x
DO - 10.1111/j.1447-0756.2010.01396.x
M3 - Article
C2 - 21375666
AN - SCOPUS:80052770836
SN - 1341-8076
VL - 37
SP - 553
EP - 562
JO - Journal of Obstetrics and Gynaecology Research
JF - Journal of Obstetrics and Gynaecology Research
IS - 6
ER -