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Determinants of maternal breast milk cortisol increase: Examining dispositional and situational factors.
Vacaru, Stefania V; Brett, Bonnie Erin; Eckermann, Henrik; de Weerth, Carolina.
Afiliação
  • Vacaru SV; Radboud university medical centre, Donders Institute for Brain, Cognition and Behaviour, Department of Cognitive Neuroscience, Nijmegen, the Netherlands; Vrije Universiteit Amsterdam, the Netherlands. Electronic address: stefania.vacaru@radboudumc.nl.
  • Brett BE; Radboud university medical centre, Donders Institute for Brain, Cognition and Behaviour, Department of Cognitive Neuroscience, Nijmegen, the Netherlands.
  • Eckermann H; Radboud university medical centre, Donders Institute for Brain, Cognition and Behaviour, Department of Cognitive Neuroscience, Nijmegen, the Netherlands.
  • de Weerth C; Radboud university medical centre, Donders Institute for Brain, Cognition and Behaviour, Department of Cognitive Neuroscience, Nijmegen, the Netherlands.
Psychoneuroendocrinology ; 158: 106385, 2023 12.
Article em En | MEDLINE | ID: mdl-37757597
BACKGROUND: Breast milk is a rich nutritional source, containing numerous proteins, carbohydrates, and hormones that impact long-term offspring development. Strikingly, predictors and correlates of breast milk composition remain largely unknown. Building on a previously discovered increase in breast milk cortisol concentration from 2 to 12 weeks postpartum, we investigated potential predictors of maternal breast milk cortisol in the first three months post-delivery by examining a suite of maternal dispositional (e.g., attachment, adverse childhood experiences or ACEs) and situational factors (e.g., partner support, self-efficacy). METHODS: Data from 73 mothers were collected prenatally, at birth, and 2-, 6- and 12 weeks postpartum. The analyses, which sought to predict postnatal changes in breast milk cortisol, included a pool of theoretically-sound constructs (Table 1) and an exploratory data-driven approach. We fit models differing in complexity as preregistered: 1) Random Forest models, capable of modeling interactions and non-linear relationships, and 2) Bayesian linear models, allowing to model change over time while less prone to overfitting. RESULTS: Overall, we found that no single variable had strong predictive value beyond the known predictors of cortisol, such as time since awakening and time of collection. However, results from both models suggest that ACEs carry information that warrants future investigations, pointing towards a negative relationship with cortisol concentration in breast milk, albeit with a minimal effect size. CONCLUSION: Using sophisticated models, we found that early life stress may play a role in physiological stress markers in breast milk in the first three months postpartum, with potential implications for offspring development.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Hidrocortisona / Leite Humano Tipo de estudo: Prognostic_studies Limite: Female / Humans / Newborn Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Hidrocortisona / Leite Humano Tipo de estudo: Prognostic_studies Limite: Female / Humans / Newborn Idioma: En Ano de publicação: 2023 Tipo de documento: Article