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Differential Eating Disorder Symptom Trajectories Across the Perinatal Period and Associated Psychosocial Factors
Caroline Christian1, Lydia B Brown1, Christine C Call1
1Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.
Background:
The perinatal period is a critical risk period for changes in eating disorder (ED) symptoms. However, extant research is mixed regarding the direction of these changes, with some studies identifying relief from ED symptoms and others finding evidence of worsening symptoms during this time. To account for heterogeneity in ED symptom change among pregnant and postpartum individuals, the current study aimed to explore ED symptom trajectories and their psychosocial correlates during pregnancy and the first postpartum year using person-centered statistical approaches.
Method:
A community sample of pregnant people recruited online (N = 315) completed assessments of ED symptoms and psychosocial factors during pregnancy, 8-weeks postpartum, and 1-year postpartum between October 2020 and January 2023. ED symptom trajectories were identified using group-based multivariate trajectory modeling. Multinomial logistic regression tested if psychosocial factors (anxiety, depression, stress, emotion regulation difficulties, self-compassion, social support, and body mass index) during pregnancy and across postpartum were associated with trajectory groups.
Results:
Four distinct groups were identified: decreasing ED cognitions group (34% of the sample), increasing ED symptoms group (29%), early postpartum ED risk group (22%), and early postpartum alleviation group (15%). Postpartum weight retention and increasing depression from pregnancy to 1-year postpartum were associated with higher odds of membership in the increasing ED symptoms group, relative to other groups.
Discussion:
Although perinatal ED symptoms were commonly endorsed, symptom changes were heterogeneous. It is important to continue to investigate prospective correlates of perinatal ED symptoms and utilize idiographic modeling to inform prevention and early intervention approaches.
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