Food insecurity risk and alcohol use disorder in US young adults: Findings from the National Longitudinal Study of Adolescent to Adult Health
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: The relationship between food insecurity and alcohol use disorder remains unknown. The aim of this study was to determine the association between food insecurity risk and alcohol use disorder in a nationally representative sample of young adults. METHODS: Cross-sectional nationally representative data of 14,786 US young adults aged 24-32 years old from Wave IV (2008) of the National Longitudinal Study of Adolescent to Adult Health were analyzed to assess a single-item measure of food insecurity risk and Diagnostic and Statistical Manual, 5th Edition (DSM-5) alcohol use disorder. RESULTS: Among young adults, 12% were found to be at risk for food insecurity. Young adults with food insecurity risk had greater odds of moderate (adjusted odds ratio [AOR]: 1.34, 95% confidence interval [CI]: 1.13-1.58) and severe (AOR: 1.67, 95% CI: 1.34-2.07) threshold alcohol use disorder than food-secure young adults, adjusting for age, sex, race/ethnicity, education, income, receipt of public assistance, household size, and smoking. Food insecurity risk was also associated with a 23% higher (95% CI: 11%-37%) number of problematic alcohol use behaviors (e.g., risky behaviors, continued alcohol use despite emotional or physical health problems). DISCUSSION AND CONCLUSIONS: Food insecurity risk is associated with problematic patterns of alcohol use. Health care providers should screen for food insecurity and problematic alcohol use in young adults and provide referrals for further resources and treatment when appropriate. SCIENTIFIC SIGNIFICANCE: This nationally representative study of US young adults is the first to find an association between food insecurity risk and alcohol use disorder using DSM-5 criteria.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".