Psychosocial stress and longitudinally measured gestational weight gain throughout pregnancy: The Ulm SPATZ Health Study.
S BraigC A LoganF ReisterD RothenbacherJon GenuneitPublished in: Scientific reports (2020)
Psychosocial stress is thought to influence gestational weight gain (GWG), but results are inconsistent. We investigated the relationship of questionnaire-based maternal stress and related constructs assessed at childbirth with maternal weight measured throughout pregnancy. Data were derived from the Ulm SPATZ Health Study, a birth cohort recruited from the general population (04/2012-05/2013, Ulm, Germany). Adjusted generalized estimating equations were performed. Regression coefficients (b) and 95% confidence intervals, each highest versus lowest tertile of stress or related constructs, are presented. In 748 women, we observed positive associations for maternal chronic stress (b = 4.36 kg (1.77; 6.95)), depressive symptoms (b = 2.50 kg (0.14; 4.86)), anxiety symptoms (b = 3.26 kg (0.62, 5.89)), and hair cortisol (b = 3.35 kg (0.86; 5.83)) with maternal weight at the first gestational month. GWG was considerably lower in mothers with higher chronic stress. Pregnancy-related anxiety was positively related to weight at first month (b = 4.16 kg (1.74; 6.58)) and overall GWG. In contrast, no association was observed between anxiety symptoms and GWG. Odds ratios for association with inadequate weight gain according to Institute of Medicine recommended cutoffs differed from the results presented obove. There is evidence of an association between stress and weight gain lying beyond the recommended cut-offs, which however needs further corroboration.
Keyphrases
- weight gain
- birth weight
- body mass index
- pregnancy outcomes
- weight loss
- mental health
- depressive symptoms
- public health
- healthcare
- computed tomography
- type diabetes
- preterm birth
- drug induced
- metabolic syndrome
- risk assessment
- skeletal muscle
- gestational age
- machine learning
- health information
- heat stress
- magnetic resonance imaging
- social media
- magnetic resonance
- social support
- cross sectional
- data analysis
- health promotion