Relationship between daily affect and overeating-only, loss of control eating-only, and binge eating episodes in obese adults

Kelly C. Berg, Carol B. Peterson, Ross D. Crosby, Li Cao, Scott J. Crow, Scott G. Engel, Stephen A. Wonderlich

Research output: Contribution to journalArticlepeer-review

29 Scopus citations

Abstract

The two objectives of the current study were: (1) to identify daily patterns of negative affect (NA) in obese individuals; and (2) to determine whether daily affect patterns were related to overeating without loss of control (OE-only), loss of control eating without overeating (LOC-only), and binge eating (BE) episodes. Fifty obese (BMI=40.3±08.5) adults (84.0% female) completed a two-week ecological momentary assessment protocol during which they completed assessments of NA and indicated whether their eating episodes were characterized by OE and/or LOC. Latent growth mixture modeling (LGMM) was used to identify daily trajectories of NA. GEE analysis was used to determine whether daily affect trajectories were differentially related to the frequency of OE-only, LOC-only, and BE episodes. The LGMM analyses identified nine unique trajectories of NA. Significantly higher frequencies of OE-only and BE episodes occurred on days characterized by high or increasing levels of NA. There were no significant differences between classes for the frequency of LOC-only episodes. These data suggest that NA may act as an antecedent to OE-only and BE episodes and that targeting "problematic affect days" may reduce the occurrence of OE-only and BE episodes among obese individuals.

Original languageEnglish (US)
Pages (from-to)185-191
Number of pages7
JournalPsychiatry Research
Volume215
Issue number1
DOIs
StatePublished - Jan 30 2014

Bibliographical note

Funding Information:
The authors would like to acknowledge Nora Durkin, M.A. and Heather Beach, M.P.H. for their help with data collection. This research was supported by Grants from NIDDK ( P30DK 50456 ) and NIMH ( T32 MH082761-01 ).

Keywords

  • Latent growth mixture modeling
  • Mood
  • Obesity

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