Socioeconomic Disadvantage across the Life Course Is Associated with Diet Quality in Young Adulthood
Bibliographic record
Abstract
Socioeconomic position (SEP) is a key determinant of diet quality across the life course. Young adulthood is a unique period of transition where dietary inequities between groups with lower and higher SEP may widen. This study investigated associations between SEP in both childhood and young adulthood and diet quality in young adulthood. Data from 1949 Canadian young adults aged 18⁻30 who participated in the Canada Food Study were analyzed. Healthy Eating Index⁻2015 (HEI-2015) scores were calculated based on one 24-hour dietary recall. Childhood and young adult SEP were represented by self-report of participants' parent(s)' and their own highest educational level, respectively. Linear regression was used to examine associations between childhood and adult SEP and adult HEI-2015 score. Mediation analyses examined whether adult SEP mediated the relationship between childhood SEP and adult HEI-2015 score. Lower SEPs in childhood and adulthood were each associated with lower HEI-2015 scores in young adulthood. Adult SEP mediated up to 13.0% of the association between childhood SEP and adult HEI-2015 scores. Study findings provide support for key life course hypotheses and suggest latent, pathway, and cumulative effects of SEP across the early life course in shaping the socioeconomic patterning of diet quality in young adulthood.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".