Is There an Association Between High or Low Weight Gain and Maternal and Infant Outcomes?
BACKGROUND AND PURPOSE:
Most women in the United States significantly increase their caloric consumption during pregnancy, with many exceeding the recommended IOM guidelines
Goldstein et al. (JAMA, 2017) conducted a systematic review comparing women who gained more or less than the recommended 2009 IOM guidelines to determine if there is actually an association with maternal and infant outcomes
Systematic review and meta-analysis
1,309,136 pregnant women were included among 23 studies that met inclusion criteria
Small for gestational age (SGA)
Large for gestational age (LGA)
Gestational weight gain was below IOM guidelines in 23% of pregnancies and above guidelines in 47%
Woman who exceeded weight gain guidelines had
Lower risk for SGA (odds ratio 0.66; 95% CI 0.55-0.64)
Lower risk for preterm birth (odds ratio 0.77; 95% CI 0.69-0.86)
Higher risk for LGA (odds ratio 1.85; 95% CI 1.76-1.95)
Higher risk for macrosomia (odds ratio 1.95; 95% CI 1.79-2.11)
Higher risk for cesarean delivery (odds ratio 1.30; 95% CI 1.25-1.35)
Woman who gained less weight than guidelines had
Higher risk for SGA (odds ratio 1.53; 95% CI 1.44-1.64)
Higher risk for preterm birth (odds ratio 1.70; 95% CI 1.32 – 2.20)
Lower risk for LGA (odds ratio 0.59; 95% CI 0.55-0.64)
Lower risk for macrosomia (odds ratio 0.60; 95% CI 0.52-0.68)
No difference in cesarean delivery
Data was not adequate to assess GDM
Both low and high weight gain outside the IOM targets were associated with adverse outcomes in both mother and infants
The authors point out that this study assessed association and not causation
Friedmann and Balayla applied a novel model to address gestational age bias (see ‘Learn More – Primary Sources’ below)
Analysis of over approximately 1.5 million women with normal prepregnancy weight did not demonstrate increased risk of infant death in the first year of life among those with excessive or inadequate weight gain using the IOM standards
The authors suggest that their novel analytic model may be helpful in future research on BMI and weight gain
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