Journal article
Lukas A. Basedow, Sören Kuitunen-Paul, Veit Roessner, Gunther H. Moll, Yulia Golub, Anna Eichler
BMC Psychiatry, vol. 22, 2022 Oct, p. 668
BMC Psychiatry, vol. 22, 2022 Oct, p. 668
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APA
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Basedow, L. A., Kuitunen-Paul, S., Roessner, V., Moll, G. H., Golub, Y., & Eichler, A. (2022). Are perinatal measures associated with adolescent mental health? A retrospective exploration with original data from psychiatric cohorts. BMC Psychiatry, 22, 668.
Chicago/Turabian
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Basedow, Lukas A., Sören Kuitunen-Paul, Veit Roessner, Gunther H. Moll, Yulia Golub, and Anna Eichler. “Are Perinatal Measures Associated with Adolescent Mental Health? A Retrospective Exploration with Original Data from Psychiatric Cohorts.” BMC Psychiatry 22 (October 2022): 668.
MLA
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Basedow, Lukas A., et al. “Are Perinatal Measures Associated with Adolescent Mental Health? A Retrospective Exploration with Original Data from Psychiatric Cohorts.” BMC Psychiatry, vol. 22, Oct. 2022, p. 668.
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@article{basedow2022a,
title = {Are perinatal measures associated with adolescent mental health? A retrospective exploration with original data from psychiatric cohorts},
year = {2022},
month = oct,
journal = {BMC Psychiatry},
pages = {668},
volume = {22},
author = {Basedow, Lukas A. and Kuitunen-Paul, Sören and Roessner, Veit and Moll, Gunther H. and Golub, Yulia and Eichler, Anna},
month_numeric = {10}
}
ABSTRACT Background: Perinatal markers of prenatal development are associated with offspring psychiatric symptoms. However, there is little research investigating the specificity of perinatal markers for the development of specific disorders. This study aimed to explore if perinatal markers are specifically associated with adolescent substance use disorder (SUDs).
Methods: Adolescent participants from two study centers, one for SUD patients (n = 196) and one for general psychopathology (n = 307), were recruited for participation. Since the SUD participants presented with a number of comorbid disorders, we performed a 1-on-1 matching procedure, based on age, gender, and specific pattern of comorbid disorders. This procedure resulted in n = 51 participants from each group. From all participants and their mothers we recorded perinatal markers (mode of birth, weeks of completed pregnancy, birth weight, Apgar score after 5 min) as well as intelligence quotient (IQ). The SUD sample additionally filled out the Youth Safe Report (YSR) as well as the PQ-16 and the DUDIT. We aimed to distinguish the two groups (SUD sample vs. general psychiatric sample) based on the perinatal variables via a logistic regression analysis. Additionally, linear regressions were performed for the total group and the subgroups to assess the relationship between perinatal variables and IQ, YSR, DUDIT and PQ-16.
Results: The perinatal variables were not able to predict group membership (X2 [4] = 4.77, p = .312, Cox & Snell R² = 0.053). Odds ratios indicated a small increase in probability to belonging to the general psychiatric sample instead of the SUD sample if birth was completed via C-section. After Bonferroni-correction, the linear regression models showed no relation between perinatal markers and IQ (p = .60, R² = 0.068), YSR (p = .09, R² = 0.121), DUDIT (p = .65, R² = 0.020), and PQ-16 (p = .73, R² =0.021).
Conclusion: Perinatal markers were not able to distinguish SUD patients from patients with diverse psychopathologies. This pattern contradicts previous findings, perhaps because our chosen markers reflect general processes instead of specific mechanistic explanations. Future studies should take care to investigate specific prenatal markers and associate them with psychopathology on the symptom level.
Methods: Adolescent participants from two study centers, one for SUD patients (n = 196) and one for general psychopathology (n = 307), were recruited for participation. Since the SUD participants presented with a number of comorbid disorders, we performed a 1-on-1 matching procedure, based on age, gender, and specific pattern of comorbid disorders. This procedure resulted in n = 51 participants from each group. From all participants and their mothers we recorded perinatal markers (mode of birth, weeks of completed pregnancy, birth weight, Apgar score after 5 min) as well as intelligence quotient (IQ). The SUD sample additionally filled out the Youth Safe Report (YSR) as well as the PQ-16 and the DUDIT. We aimed to distinguish the two groups (SUD sample vs. general psychiatric sample) based on the perinatal variables via a logistic regression analysis. Additionally, linear regressions were performed for the total group and the subgroups to assess the relationship between perinatal variables and IQ, YSR, DUDIT and PQ-16.
Results: The perinatal variables were not able to predict group membership (X2 [4] = 4.77, p = .312, Cox & Snell R² = 0.053). Odds ratios indicated a small increase in probability to belonging to the general psychiatric sample instead of the SUD sample if birth was completed via C-section. After Bonferroni-correction, the linear regression models showed no relation between perinatal markers and IQ (p = .60, R² = 0.068), YSR (p = .09, R² = 0.121), DUDIT (p = .65, R² = 0.020), and PQ-16 (p = .73, R² =0.021).
Conclusion: Perinatal markers were not able to distinguish SUD patients from patients with diverse psychopathologies. This pattern contradicts previous findings, perhaps because our chosen markers reflect general processes instead of specific mechanistic explanations. Future studies should take care to investigate specific prenatal markers and associate them with psychopathology on the symptom level.
