New research from Pitt helps predict depression during pregnancy, bringing faster help

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We hear a lot about postpartum depression, but about 15% of women develop depression during pregnancy — not just after the baby is born. Now, researchers at the University of Pittsburgh developed a way to identify who will likely develop depression during pregnancy.

The researchers at Pitt developed a machine-learning algorithm that could predict with excellent accuracy which pregnant women, who had no history of depression, would develop depression in the second or third trimesters.

Dr. Tamar Krishnamurti says they found that certain factors were key predictors of depression.

“Worrying about financial stability or running out of food concerns about an individual’s ability to kind of manage their ongoing health problems,” were some of the predictors, Dr. Krishnamurti said.

“We found that some worries that were specific to pregnancy were predictive, so things like feeling stressed about their upcoming labor and delivery or worrying about how their new baby might affect their interpersonal relationships.”

Depression is one of the leading complications of pregnancy, and suicide is a leading cause of death among pregnant women.

Dr. Krishnamurti is hopeful this can help reduce that.

“The sooner that we know someone’s at risk for depression, the earlier we can offer different preventive care options, whether that’s therapy or peer support, or even tangible things like providing meals or taking major stresses out of people’s lives.”

Dr. Krishnamurti says this is the first tool to predict depression during pregnancy, rather than identify it once it starts. The researchers are now creating a screener that any healthcare provider can use to predict which pregnant women may develop depression and to get them the help they need.