Steep discounting of delayed monetary and food rewards in obesity: a meta-analysis
Abstract
Background: An increasing number of studies have investigated delay discounting (DD) in relation to obesity, but with mixed findings. This meta-analysis synthesized the literature on the relationship between monetary and food DD and obesity, with three objectives: (1) to characterize the relationship between DD and obesity in both case–control comparisons and continuous designs; (2) to examine potential moderators, including case–control v. continuous design, money v. food rewards, sample sex distribution, and sample age (<18 v. >18 years); and (3) to evaluate publication bias. Method: From 134 candidate articles, 39 independent investigations yielded 29 case–control and 30 continuous comparisons (total n = 10 278). Random-effects meta-analysis was conducted using Cohen's d as the effect size. Publication bias was evaluated using fail-safe N, Begg–Mazumdar and Egger tests, meta-regression of publication year and effect size, and imputation of missing studies. Results: The primary analysis revealed a medium effect size across studies that was highly statistically significant ( d = 0.43, p < 10 −14 ). None of the moderators examined yielded statistically significant differences, although notably larger effect sizes were found for studies with case–control designs, food rewards and child/adolescent samples. Limited evidence of publication bias was present, although the Begg–Mazumdar test and meta-regression suggested a slightly diminishing effect size over time. Conclusions: Steep DD of food and money appears to be a robust feature of obesity that is relatively consistent across the DD assessment methodologies and study designs examined. These findings are discussed in the context of research on DD in drug addiction, the neural bases of DD in obesity, and potential clinical applications.
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Discount rate is highly correlated with a variety of health behaviors and disorders, with medium effect sizes across studies.
“Supporting this belief, discount rate is highly correlated with a variety of health behaviors and disorders, with medium effect sizes across studies (Amlung, Petker, Jackson, Balodis, & MacKillop, 2016; Jackson & MacKillop, 2016; MacKillop et al., 2011).”
From Behavioral trainings and manipulations to reduce delay discounting: A systematic review (2019) · cites this paper as Amlung et al., 2016
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Self-citation
- Authors
- Amlung, M., Petker, T., Jackson, J., Balodis, I., & MacKillop, J.
- Affiliations
- Peter Boris Centre for Addictions Research (CA)
- Homewood Research Institute (CA)
- Corresponding author
- Amlung, M.
- Venue
- Psychological Medicine
- Publisher
- Cambridge University Press (CUP)
- Published
- 2016-06-15
- Volume
- 46
- Issue
- 11
- Pages
- 2423-2434
- ISSN
- 0033-2917 (ISSN-L)
- 1469-8978
- OpenAlex
- W2431859568
- Cited by
- 274
- References
- 82
- Citations by year
- 2026: 18 · 2025: 22 · 2024: 28 · 2023: 34 · 2022: 26 · 2021: 39 · 2020: 32 · 2019: 27 · 2018: 24 · 2017: 20 · 2016: 4
- FWCI
- 3.73
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Psychological Medicine (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institutes of Health
- National Institute on Drug Abuse (P30DA027827)
- Topics
- Social Sciences › Decision Sciences › General Decision Sciences › Decision-Making and Behavioral Economics
- Social Sciences › Psychology › Clinical Psychology › Eating Disorders and Behaviors
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Obesity, Physical Activity, Diet
- Keywords
- delay discounting, obesity, food reward, monetary rewards, impulsivity, adolescents, publication bias
- MeSH terms
- Food, Humans, Obesity, Reward, Delay Discounting
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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