The Relationship between Music and Food Intake: A Systematic Review and Meta-Analysis
Abstract
Food intake has been shown to be related to several environmental factors including the presence of music. However, previous findings of the relationship between music and food intake are inconsistent. In the present study, a systematic review and meta-analysis was conducted to quantitatively review the extent to which music is associated with food intake as well as to investigate potential moderators that might have contributed to the heterogeneity of the existing findings. Literature was searched on four databases (i.e., PsycINFO, Web of Science, PubMed, and ProQuest Dissertations and Theses) and Google Scholar. Nine articles published from 1989 to 2020 met our inclusion criteria. A meta-analysis was carried out via a three-level random-effects model. The overall effect size (i.e., Hedges’ g) was 0.19 (95% Confidence Interval: −0.003, 0.386; SE = 0.10, t = 1.99, p = 0.054), indicating a marginally significant but small effect size. Body Mass Index (F(1, 21) = 5.11, p = 0.035) was found to significantly contribute to the heterogeneity of effect sizes, with larger positive effects of music on food intake for individuals with higher BMI. However, music-related features did not significantly moderate the relationship between music and food intake. More experimental studies are needed to update the current meta-analysis and get a better understanding of this topic.
CUI Tianxiang
PhD Student in Psychology
My research interests include body image, eating behaviors, quantitative methods in psychology, and music psychology.
TANG Chanyuan
Former Graduate Advisee
TANG Chanyuan is a research assistant in applied psychology at The Chinese University of Hong Kong, Shenzhen, working under Prof. HE Jinbo’s supervision.
SONG Jianwen
PhD Student in Educational Psychology
HE Jinbo
Assistant Professor in Applied Psychology
My research interests include the mental health of children and adolescents, obesity, eating behaviors, eating disorders, body image, and various advanced quantitative research methods (e.g., structural equation modeling, latent growth curve modeling, finite mixture modeling, meta-analysis).