Monday’s Briefs: Quick musings on child related research.

Editor’s note: Due to the yesterday especial editorial on bullying and suicide, Monday’s brief comes to you a date late. Wednesday’s post will be published tomorrow as expected. We will review the latest study on vaccines and autism.

The leading causes of childhood disabilities are prenatal and neonatal complications, such as preterm birth, low birth weight, and intrauterine growth restriction. There are multiple factors that can lead to these complications, such as smoking, drinking, and experiencing some medical conditions.  Some studies have suggested that maternal depression can increase the risk for these complications but other studies have found that depression has no impact on these complications. Why the discrepancy? The latest issue of the prestigious journal Archives of General Psychiatry included a comprehensive meta-analysis of the association between depression during pregnancy and birth complications. In the meta-analysis, the authors merged the results previous studies on this topic in order to examine factors that could explain the differences between the studies.

Among the many factors that the authors examined, I want to focus on a specific issue: whether the previous studies measured depression as a categorical construct (e.g., comparing mothers who met diagnostic criteria for a depressive disorder against those who didn’t meet criteria) or as a continuous construct (comparing those with more symptoms of depression to those with less symptoms of depression). Overall, the authors found the following:

Effects of Depression on Pre-Term Birth:

Depression during pregnancy, when measured as a categorical construct, increased the risk for pre-term birth by 39%. In contrast, depression symptoms increased the risk by only 3%.

Effects of Depression Low Birth Weight:

Depression during pregnancy, when measured as a categorical construct, increased the risk for low birth weight by 49%. In contrast, depression symptoms did not impact the risk for low birth weight.

Effects of Depression on Intrauterine Growth Restriction:

Depression during pregnancy, when measured as a categorical construct, increased the risk for intrauterine growth restriction by 45%. In contrast, depression symptoms did not impact the risk for intrauterine growth restriction.

These results suggest that having some symptoms of depression may not increase the risk of birth complications. However, having clinical depression significantly increases the risk for complications. This is not entirely surprising since there are significant differences between experiencing symptoms of depression, many of which are common and normative, and having a diagnosed depressive disorder. In this case, it seems that having a depressive disorder is a risk factor for prenatal and neonatal complications. This highlights the need to screen for depression during pregnancy so that those affected can receive treatment.

The authors concluded:

Clearly, pregnancy is an important time to universally screen women for depression, especially those who are socioeconomically disadvantaged, and to improve their timely access to evidence-based prenatal and mental health services. Improved accuracy of diagnosis and treatment of antenatal depression combined with education about harmful but potentially modifiable lifestyle practices could lead to decreased rates of PTB and LBW.

The reference:

Grote, N., Bridge, J., Gavin, A., Melville, J., Iyengar, S., & Katon, W. (2010). A Meta-analysis of Depression During Pregnancy and the Risk of Preterm Birth, Low Birth Weight, and Intrauterine Growth Restriction Archives of General Psychiatry, 67 (10), 1012-1024 DOI: 10.1001/

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3 Responses to Depression during pregnancy and birth complications.

  1. RAJ says:


    This study was a mega-analysis. Sir Michael Rutter who is considered to be the father of modern child and adolescent psychiatry has stated that all science is provisional and where the evidence has not been established you can never, ever, accept established science in terms of a football score analogy which all of these mega-anaylsis studies are. If seven studies say yes and three studies say no the yes wins.

    One of Michael Rutter areas of interest is in the causes of autism. He served as the European editor of the Journal of Autism and Developmental Disorders until his retirement in the 1990′s although he is still active and regularly sees patients and travels the world giving keynote addresses at scientific conferences.
    If you had conducted a study on the causes of autism in 1965 using a meta-analysis of published studies and asked the quesion ‘Is autism caused by the maternal emotional rejection of the infant?’

    The football score would have been 42 Yes and 3 No, the Yes wins.

    Caution is warrented in accepting the validty of mega-analysis.

    • I’m 100% in agreement RAJ. Meta-analyses help us understand the STATUS of knowledge to date, but it does not imply that the science would not move forward and the results change as we learn more about a specific condition, etc. However, it is not quite accurate that if 7 studies say yes and 3 say no, the yes would win. There are many cases where “No” would win (e.g., the 3 studies have significantly larger samples and lower error bands than the 7 studies). So it is not simply a matter of counting studies. Also, often I find it to be a slippery slope to differentially accept or ignore science’s current understanding of a topic (to fit our beliefs) under the argument that science always changes. I am concerned because it facilitates a major error: selecting the lest supported option because the evidence for the most supported option is not perfect

  2. RAJ says:

    “I am concerned because it facilitates a major error: selecting the lest supported option because the evidence for the most supported option is not perfect”

    Actually, I wouldn’t support either option when there is significant dispute in results and different intepretations of the same data. The study you refer to deserves the Scottich verdict of ‘not proven’. Mega-analysis may be more meaningful in the hard sciences (eg physics) where you can measure physical attibutes but not so much in the behavioral sciences (eg. psychology).

    Kanner, in his preface to his 1943 article ‘Autistic Disturbances of Affective Contact’ quoted Rose Zelig:

    ‘To understand and measure emotional qualities is very difficult. Psychologists and educators have been struggling with that problem for years but we are still unable to measure emotional and personality traits with the exactness with which we can measure intelligence’.

    This is as true today as it was 80 years ago. I guess we will just have to disagree on the meaningfulness of the study you discuss.

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