4.5 Article

Psychological stress and cortisol during pregnancy: An ecological momentary assessment (EMA)-Based within- and between-person analysis

Journal

PSYCHONEUROENDOCRINOLOGY
Volume 121, Issue -, Pages -

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.psyneuen.2020.104848

Keywords

Ecological Momentary Assessment (EMA); Stress; Cortisol; Pregnancy; Linear mixed modelling; Psychoendocrine covariance

Funding

  1. US PHS (NIH) [R01 HD-060628, R01 AG-050455, R01 HD-065825, UH3 OD-O23349]
  2. European Research Council [ERC-Stg 678073]

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Background: Although the linkage between psychological stress and cortisol is believed to mediate the association of stress with health outcomes, several studies have been unable to demonstrate this association. We suggest this inability may be a consequence of limitations in the measurement approach and/or reliance on analytic strategies that focus on associations across, rather than within individuals. The link between psychological stress and cortisol is of particular interest in the context of pregnancy and fetal development. Using an ecological momentary assessment (EMA) design, we examined the association between psychological stress and cortisol at the between- and the within-person level. Methods: 152 participants completed a 4-day long EMA protocol serially in early, mid and late pregnancy to provide momentary stress appraisals (average of 150 measures/subject) and saliva samples (average of 55 samples/subject) for quantification of cortisol. The association between stress and cortisol was estimated using linear mixed models. Results: After accounting for the effects of key determinants of variation in cortisol, momentary stress was significantly and positively associated with cortisol at the within-person level (B = .030, p = .031), but not at the between-person level. No association was evident for traditional retrospective measures of stress with cortisol at either the between- or the within-person level. Conclusions: Our study highlights the value of EMA methods and linear mixed-modeling approaches in linking maternal psychological and physiological states across pregnancy. These findings may have important implications for the development of personalized risk identification and just-in-time intervention strategies to optimize maternal and child health.

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