Social support and C-reactive protein in a Québec population cohort of children and adolescents
Bibliographic record
Abstract
OBJECTIVE: Robust evidence exists for the health-enhancing benefits of social support in adults. Inflammatory processes are thought to be an important mechanism linking social support and health risk. Less is known about the relation between social support and chronic inflammation during childhood and adolescence, or when the association emerges during the lifespan. METHOD: Data from the population-representative 1999 Quebec Child and Adolescent Health and Social (QCAHS) survey were analyzed. Youth aged 9, 13, and 16 years (N = 3613) and their parents answered questions about social support. A subsample (n = 2186) completed a fasting blood draw that was assayed for C-reactive protein (CRP). FINDINGS: Higher social support was significantly associated with lower hs-CRPlog, after controlling for age, sex, body mass index (BMI Z-score), medication use, puberty, ethnoracial status (French-Canadian), smoking, household income, and parental education (F = 25.88, p = < .001, Total R2adj = 10.2%). The association was largely similar for boys and girls, and strengthened with age. CONCLUSION: Greater social support was linked to lower chronic low-grade inflammation in a large sample of children and adolescents. Effect sizes were small and consistent with prior findings in the adult literature. Importantly, these findings provide evidence that the relation between social support and inflammation emerges early in the lifespan. Future work should consider broader, more encompassing conceptualizations of social support, the role of social media, and prospective trajectories of social support and inflammatory markers.
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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 | 0.001 |
| 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 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".