Life-course socioeconomic position and the gut microbiome in the Hispanic Community Health Study/Study of Latinos (HCHS/SOL)
Bibliographic record
Abstract
Socioeconomic position (SEP) in childhood and beyond may influence the gut microbiome, with implications for disease risk. Studies evaluating the relationship between life-course SEP and the gut microbiome are sparse, particularly among Hispanic/Latino individuals, who have a high prevalence of low SEP. We use the Hispanic Community Health Study/Study of Latinos (HCHS/SOL), a population-based cohort study conducted in four field centers in the United States (U.S.), to evaluate the association between life-course SEP and gut microbiome composition. Life-course SEP indicators included parental education (proxy of childhood SEP), current SEP (n = 2174), and childhood (n = 988) and current economic hardship (n = 994). Shotgun sequencing was performed on stool samples. Analysis of Compositions of Microbiomes was used to identify associations of life-course SEP indicators with gut microbiome species and functions. Parental education and current SEP were associated with the overall gut microbiome composition; however, parental education and current education explained more the gut microbiome variance than the current SEP. A lower parental education and current SEP were associated with a lower abundance of species from genus Bacteroides. In stratified analysis by nativity, we found similar findings mainly among foreign-born participants. Early-life SEP may have long-term effects on gut microbiome composition underscoring another biological mechanism linking early childhood factors to adult disease.
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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 | 0.001 |
| Science and technology studies | 0.000 | 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".