Food security and eating disorder behaviors in the International Food Policy Study, 2018 to 2022
Bibliographic record
Abstract
BACKGROUND: A link has been established between food insecurity and eating disorder (ED) pathology, but most research on this topic has occurred in the USA. This study examined associations and potential moderators of associations between food security (FS) levels and ED behaviors cross-nationally. METHODS: Repeated cross-sectional data representing 104 881 adults 18-100 years of age in Australia, Canada, Mexico, the UK, and the USA came from five waves (2018-22) of the International Food Policy Study. Participants completed the Household Food Security Survey Module and reported on past-3-month binge eating and self-induced vomiting to control weight. Associations between past-year household FS level and ED behaviors were examined with adjusted modified Poisson regression models. Interactions with potential moderators were also tested. RESULTS: Marginal, low, and very low FS were associated with elevated prevalence of both ED behaviors. Compared with households with high FS, binge eating was 1.34, 1.54, and 1.73 times as prevalent in households with marginal, low, and very low FS, respectively. Associations were stronger for self-induced vomiting; compared with households with high FS, self-induced vomiting was 2.40, 7.10, and 11.98 times as prevalent in households with marginal, low, and very low FS, respectively. Moderation results revealed meaningful differences by some factors. For example, associations were weaker in Mexico and stronger among ethnic minorities and participants with children. CONCLUSION: Results support cross-sectional associations between FS and ED behaviors, with a particularly strong link for self-induced vomiting. Some heterogeneity in these associations was observed across country and sociodemographic factors.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".