Adults with overweight or obesity use less efficient memory strategies compared to adults with healthy weight on a verbal list learning task modified with food words

Appetite. 2023 Feb 1:181:106402. doi: 10.1016/j.appet.2022.106402. Epub 2022 Nov 29.

Abstract

Several studies suggest poorer episodic memory among adults with overweight (OW) relative to those with healthy weight (HW); however, few have used food stimuli. To understand the salience of food-related items when assessing memory, we adapted an episodic memory task, by replacing some non-food words with snack foods. Participants were 96 weight-loss seeking adults with OW compared to 48 adults with HW from the community matched on age, gender, ethnicity, and education. Overall memory ability was similar, although a trend showed the adults with HW performed better than adults with OW on immediate recall (d = 0.32, p = 0.07). However, there were clear differences in the use of learning strategies. Adults with HW utilized sematic clustering more effectively than adults with OW during all test phases (ds = 0.44-0.62; ps ≤ 0.01). Adults with HW also utilized serial clustering more effectively (d = 0.51; p < 0.01). Adults with HW showed better semantic clustering for both food and non-food words during immediate and short delay recall (ds = 0.42-0.78; ps ≤ 0.01) but semantic clustering was only better for the non-food category at long delay (d = 0.55; p < 0.01). These results show that adults with OW utilized less efficient learning strategies throughout the task and food-related content may impact learning. Clinically, these findings may suggest that weight-loss treatments should consider incorporating the teaching of learning and memory strategies to help increase utilization of new skills.

Keywords: Episodic memory; Obesity; Semantic clustering.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Adult
  • Humans
  • Learning
  • Memory Disorders
  • Mental Recall
  • Obesity* / therapy
  • Overweight* / therapy
  • Verbal Learning