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Record W4407025823 · doi:10.1016/j.eclinm.2024.103049

The impact of weight loss interventions on disordered eating symptoms in people with overweight and obesity: a systematic review & meta-analysis

2025· review· en· W4407025823 on OpenAlexaboutno aff
Elena Tsompanaki, Dimitrios A. Koutoukidis, Gina Wren, Heather Tong, Annika Theodoulou, Danni Wang, Rebecca J. Park, Susan A. Jebb, Paul Aveyard

Bibliographic record

VenueEClinicalMedicine · 2025
Typereview
Languageen
FieldPsychology
TopicEating Disorders and Behaviors
Canadian institutionsnot available
FundersNational Institute for Health and Care Research Applied Research Collaboration Oxford and Thames ValleyNational Institute for Health and Care ResearchChina Scholarship CouncilNIHR Oxford Biomedical Research CentreUniversity of OxfordNovo Nordisk UK Research FoundationNovo Nordisk
KeywordsMedicineOverweightMeta-analysisObesityPsychological interventionWeight lossSystematic reviewMEDLINEEnvironmental healthGerontologyPhysical therapyPsychiatryEndocrinologyInternal medicine

Abstract

fetched live from OpenAlex

Background It is unclear whether weight loss interventions worsen disordered eating in people living with overweight/obesity. We aimed to systematically evaluate the association between weight loss interventions and disordered eating. Methods Six databases were searched from inception until September 2024. Trials of weight loss interventions in people with overweight/obesity were included if they reported a validated score for disordered eating on either the Eating Disorder Examination Interview or the Eating Disorder Examination Questionnaire pre- and post-intervention. Interventions included behavioural weight loss programmes (BWL) and pharmacotherapy licenced for weight loss, with or without concurrent psychological support, provided for at least 4 weeks. Pooled standardised mean differences (SMD) in scores of disordered eating were calculated using random effects meta-analyses. Risk of bias (RoB) was assessed using the Cochrane RoB 2 tool and the Newcastle–Ottawa scale for randomised and single-arm trials, respectively (PROSPERO ID: CRD42023404792). Findings Thirty-eight studies with 66 eligible arms (61 interventions: 29 BWL, 11 BWL + pharmacotherapy, 20 BWL + psychological intervention, 1 pharmacotherapy + psychological intervention) and 3364 participants in total were included. The mean weight change was −4.7 kg (95% CI: −5.7, −3.7). Compared with baseline, disordered eating scores improved by −1.47 SMD units (95% CI: −1.67, −1.27, p < 0.001, I 2 = 94%) at intervention completion (median of 4 months). Seven randomised trials that directly compared a weight loss intervention to no/minimal intervention reported an improvement of −0.49 SMD units (95% CI, −0.93, −0.04, p = 0.0035, I 2 = 73%). Sub-group analyses showed: (a) disordered eating scores improved more in people with an eating disorder at baseline compared with people without high scores, (b) no clear evidence that the association depended upon intervention type, and (c) disordered eating scores improved more in trials rated at low overall RoB. Interpretation Despite heterogeneity in effect size, weight loss interventions consistently improved disordered eating scores. These findings provide reassurance that weight loss interventions might not worsen disordered eating and may improve it. Funding Novo Nordisk UK Research Foundation Doctoral Fellowship in Clinical Diabetes.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.025
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.020
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.025
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0200.032
Bibliometrics0.0070.007
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.097
GPT teacher head0.473
Teacher spread0.376 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations15
Published2025
Admission routes1
Has abstractyes

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