Child Hunger and Long-term Adverse Consequences for Health
Bibliographic record
Abstract
OBJECTIVE: To examine the effects of hunger, an extreme manifestation of food insecurity, on subsequent health outcomes using data from the Canadian National Longitudinal Survey of Children and Youth (NLSCY). DESIGN: Longitudinal survey, 1994-2004/2005. SETTING: Canada. PARTICIPANTS: A total of 5809 children aged 10 to 15 years and 3333 youth aged 16 to 21 years. MAIN EXPOSURES: Longitudinal survey data spanning a 10-year period were analyzed using logistic regression. Measures of hunger from NLSCY cycles 1 through 5 were used to differentiate participants who were ever hungry from those who were never hungry. A 3-level variable was created to assess the effect of repeated episodes of hunger. Covariates included participants' age, sex, baseline health, and household sociodemographic characteristics. Stratified models were used to examine the relation between hunger and health among boys and girls separately. OUTCOME MEASURES: The NLCSY cycle 6 outcomes included poor general health, chronic health conditions, and asthma. RESULTS: Among children, both ever being hungry and multiple episodes of hunger were associated with poorer general health but not with chronic conditions or asthma. Higher odds of chronic conditions and of asthma were observed among youth who experienced multiple episodes of hunger compared with those who were never hungry. Associations between hunger and poorer health outcomes persisted among girls in stratified analyses. CONCLUSIONS: Children and youth who experience hunger are more likely to have poorer health, and repeated exposure appears to be particularly toxic. Our findings point to the relevance of food insecurity in childhood as a marker of vulnerability, with implications for clinical practice and advocacy.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".