Maternal anthropometry to predict small for gestational age: a meta-analysis.

Area of Science:

• Perinatal medicine
• Diagnostic accuracy research
• Public health

Background:

• Predicting small for gestational age (SGA) newborns is crucial for reducing neonatal mortality and morbidity.
• Simple, rapid, and inexpensive diagnostic tools are needed for SGA prediction.
• Maternal anthropometric measurements are potential, easily accessible indicators.

Purpose of the Study:

• To evaluate the diagnostic performance of maternal anthropometric measurements in predicting SGA newborns.
• To assess the accuracy of height, weight, body mass index, and weight gain during pregnancy as predictors.

Main Methods:

• A bivariate diagnostic meta-analysis was conducted.
• Ten databases were searched, including PubMed (MEDLINE) up to August 2014.
• Hierarchical summary receiver operating characteristic (HSROC) curves were constructed; study quality was assessed.

Main Results:

• Included studies (n=39-99) evaluated maternal height, weight, BMI, and weight gain.
• No maternal parameter demonstrated high sensitivity (0.37-0.73) or specificity (0.35-0.72).
• Diagnostic accuracy was low, with limited informational value (LR+ 1-2, LR- 0.5-1, AUC ≤0.7).

Conclusions:

• This meta-analysis found insufficient evidence to support the use of maternal anthropometric measurements for predicting SGA newborns.
• Current anthropometric measures lack the diagnostic accuracy required for reliable SGA prediction.
• Further research into more effective predictive tools is warranted.