ArticleEating and weight disorders : EWD2023
Sleep is the best medicine: assessing sleep, disordered eating, and weight-related functioning.
Article in Eating and weight disorders : EWD, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed, 1 synthesis or guideline pooled it, 5 citations in OpenAlex.
- The Association Between Disordered Eating and Sleep in Non-Clinical Populations-A Systematic Review and Meta-Analysis.Journal of sleep research · 2026Pooled it
- Eating Disorders in the Workplace.Nutrients · 2025Article
- Are Sleep Parameters and Chronotype Associated with Eating Disorder Risk? A Cross-Sectional Study of University Students in Spain.Journal of clinical medicine · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 3 institutions in 1 country.
Funding
Abstract
Sleep quality is linked to disordered eating, obesity, depression, and weight-related functioning. Most research, however, has focused on clinical populations. The current study investigated relationships between sleep quality, disordered eating, and patterns of functioning in a community sample to better understand relationships among modifiable health behaviors. Participants (N = 648) recruited from Amazon Mechanical Turk completed assessments of eating, depression, weight-related functioning, and sleep. Self-reported height and weight were used to calculate body mass index (M = 27.3, SD = 6.9). Participants were on average 37.6 years (SD = 12.3), primarily female (65.4%), and White, not Hispanic (72.7%). Over half of participants endorsed poor sleep quality, and average sleep scores were above the clinical cutoff for poor sleep quality. Sleep scores were significantly positively correlated with disordered eating, depression, and weight-related functioning, even after adjusting for age, body mass index, and sex. Multivariate regression models predicting weight-related functioning and depression showed that both sleep quality and disordered eating independently predicted depression. Sleep quality did not independently predict weight-related functioning; however, disordered eating did. To the best of our knowledge, this is the first study to assess sleep behaviors, disordered eating, and weight-related functioning in a community sample of weight diverse participants. Results indicate that most participants endorsed poor sleep quality, which was associated with disordered eating patterns, including binge eating and poorer weight-related functioning, even after controlling for body mass index, highlighting that this relationship exists across the weight spectrum. These results speak to the importance of health behavior assessment and intervention within nonclinical samples.Level of evidence Level III: evidence obtained from well-designed cohort or case-control analytic studies.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.