Cortisol reactivity to a laboratory stressor predicts increases in depressive symptoms in perinatal and nulliparous women during population-level stress.

Abigail Beech,Audrey Edelman,Tal Yatziv, Helena J V Rutherford,Jutta Joormann,Reuma Gadassi-Polack

Journal of affective disorders(2023)

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摘要
BACKGROUND:Research suggests a link between stress and depression, especially in high-risk groups. The perinatal period is known as a time of increased risk for depression and pregnancy has been associated with alterations in cortisol levels; however, limited research has assessed cortisol reactivity during pregnancy. Finally, no studies have yet examined whether cortisol reactivity predicts later depressive symptoms during a population-level stressor, such as the COVID-19 pandemic. METHODS:The current study examined whether cortisol reactivity in perinatal and nulliparous women a year before the onset of COVID-19 predicted increases in depressive symptoms during the initial stage of the pandemic. Participants were 68 women (33 pregnant, Mage = 30.6; 35 nulliparous, Mage = 28.4) who, approximately a year before COVID-19, responded to a depressive symptoms questionnaire and completed a psychosocial stress test, during which they provided salivary cortisol samples. Shortly after the onset of pandemic-related closures (April 2020; postpartum for previously pregnant participants), participants completed follow-up questionnaires assessing current depressive symptoms. RESULTS:Analyses showed that cortisol reactivity at baseline predicted increases in depressive symptoms at follow-up. Perinatal and nulliparous women did not differ in this association. LIMITATIONS:The present study was limited by a moderate sample size and heterogeneity in terms of gestational week, restricting inferences about specific stages of pregnancy. CONCLUSIONS:Our findings suggest that cortisol reactivity to a laboratory stressor is a biomarker of risk for increased depressive symptoms during ecological stress in women. Biomarkers like these increase our understanding of depression risk and may help to identify individuals in need of interventions.
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